Academic year 2021 - 2022

•     ARM-Processors and Embedded Operating Systems TX00CI69-3006 25.10.2021-19.12.2021  5 credits  (ICT19-SI-E) + -
  Learning outcomes of the course

  After completion of the course the student is able to install and configure an embedded operating systems on a hardware platform. He/she understands the principle of prioritized preemptive scheduling and is able to write programs for a multitasking environment. The student knows how to use locking and inter-process communication to implement resource efficient programs. Student is able to configure and compile kernel that is tailored to run on the target hardware. The students knows how measure and monitor system resource usage of an embedded system.

  Course contents

  - Installing an embedded operating system.
  - Configuring and compiling a kernel for a specific target hardware.
  - Configuring network and connecting the system to a network.
  - Locking in multitasking environment
  - Inter-process communication
  - Performance measurement

  Assessment criteria

  Satisfactory

  Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development.

  Good

  Students have achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Students are able to define the course concepts and models and are able to justify the analysis. The student is able to apply their knowledge in leisure, study and work situations. The student understands the importance of expertise in the field of information technology and is able to analyze his/her own expertise.

  Excellent

  Students have achieved the objectives of the course with excellent marks. Students master commendably the course subject area’s concepts and models. Students are able to make justified and fluent analysis and to present concrete development measures. The students are well prepared to apply their knowledge in leisure, study and work situations. Students are able to analyze the information technology sector expertise and the evolvement of their own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT19-SI-E

  Seats

  0 - 40

  Teacher(s)

  Keijo Länsikunnas

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     ASP.NET Core Application Development TT00DU85-3004 01.01.2022-31.12.2022  5 credits  (ATX22TV) + -
  Learning outcomes of the course

  A comprehensive course to learn about ASP.NET Core. The goal of this course is for the student to be familiar with ASP.NET Core as an open-source web framework, with having higher performance than ASP.NET. After passing this course, the student will have sufficient knowledge and understanding over characteristics, abilities, and features of ASP.NET Core. The students will be able to create a whole new project and work with all the major ASP.NET Core abilities.
  This course is 100% virtual thanks to the comprehensive content made for this course.
  The student will pass this course after submitting required assignments, quizzes, projects, and essays.

  Course contents

  Compression between ASP.NET Web Forms, MVC, and Core Advantages of ASP.NET Core – Creating ASP.NET Projects - Understanding the project structure - The Program class – Error Handling and middleware – Hosting Environment – MVC Pattern – Routing and its benefits – Rendering HTML and Razor views - Dependency Injection – Database access and Entity Framework - Security and identity

  Assessment criteria

  Satisfactory

  - The students understand the general idea about ASP.NET Web Forms, MVC, and Core
  - The student can create ASP.NET Core projects.
  - The students understand the project structure.
  - The student understands MVC pattern.

  Good

  - The student is familiar with the program class.
  - The student understands Error Handling and middleware.
  - The student can benefit from Hosting Environment.
  -The student knows how to use Routing.
  - The student can easily render HRML using Razor views

  Excellent

  - The student can fully take advantage of Dependency Injection
  - The student fully understands database access and Entity Framework.
  - The student understands Security and identity in ASP.NET Core

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  N/A

  Planned learning activities and teaching methods

  - Tutorial Videos
  - Assignments
  - Quiz
  - Projects
  - Self-study

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student - course is online (Self-Study) course.

  International connections

  N/A

  Students use of time and load

  Up to Student - course is online (Self-Study) course.

  Content periodicity

  Up to Student - course is online (Self-Study) course.

  Location and Time

  Up to Student - course is online (Self-Study) course.

•     AWS Machine Learning (not translated) TT00EV97-3001 01.08.2021-31.07.2022  5 credits  (DiplomaMD) + -
  Learning outcomes of the course

  AWS Machine Learning services provide anybody with access to the same cloud-based machine learning resources used by Amazon's own developers for machine learning implementations. It offers developers and data scientists various resources to help build their knowledge of machine learning in the AWS Cloud. This course will teach you how to get started with AWS Machine Learning and focuses on standardized approaches to data analytics and machine learning implementation based on AWS Machine Learning tools. By the end of this course, the student will learn to build, train, deploy, automate, manage, and track enterprise-grade machine learning models from scratch in a simplified way using powerful AWS tools.

  Prerequisites and co-requisites

  Fundamentals of Machine Learning or Machine Learning with python

  Course contents

  1. Introduction:
  Basics of Machine Learning – Importance of Data – Types of Machine Learning – Machine Learning Pipeline – Machine Learning Implementation – Why Cloud-based Services? – Amazon Web Services (AWS)
  
  2. AWS Machine Learning:
  What is AWS Machine Learning Service? – AWS AI Services – Amazon SageMaker – SageMaker Studio – SageMaker Autopilot – SageMaker Studio Notebooks – SageMaker Pipelines – Quiz
  
  3. Getting Started with AWS:
  AWS Pricing – Compute Instance Types – AWS Free Tier Account – Create a Free Tier Account – A Tour of AWS Interface – IAM Service – Getting Started with AWS: Exercise
  
  4. Amazon S3:
  Introduction to S3 – Set Up Amazon S3 – Create a Bucket –, Download, and Copy an Object – Properties for an S3 Bucket – Bucket Permissions – Accessing a Bucket – Storage Tier and Data Lifecycle – Delete an Object or a Bucket – Amazon S3: Exercise – Amazon S3: Quiz
  
  5. Amazon SageMaker Autopilot:
  Set up Amazon SageMaker Studio – Getting Started with SageMaker Autopilot – Create a SageMaker Autopilot Experiment – Problem Types – Model Support and Validation – Model Deployment – Models Generated by SageMaker Autopilot – Notebooks Generated by SageMaker Autopilot – Configure Inference Output – SageMaker Autopilot Quotas
  
  6. Amazon SageMaker Autopilot: Practical Example:
  Open SageMaker Studio – Load the Dataset – Create an Experiment – Explore the Experiment – Data Exploration Notebook – Deploy the Best Model – Predict with Your Model – Job Profile – Trials: Deploy the Best Model – Inference on SageMaker Console: Endpoints – on SageMaker Console: Training Job
  6.12. Training on SageMaker Console: Hyperparameter Tuning Jobs – Delete Endpoints Manually – Project 1

  Assessment criteria

  Satisfactory

  - The student is familiar with cloud-based services.
  - The student is familiar with different services that AWS offers for AI and Machine Learning.
  - The student is familiar with Amazon SageMaker.
  - The student is familiar with the concept of Automated Machine Learning (AutoML) as well as the SageMaker Autopilot for using AutoML capabilities.
  - The student is familiar with SageMaker Studio, how to create Notebooks in Studio, and how to use the basic functionalities of the Studio.
  - The student is familiar with creating a free-tier AWS account and setting up compute instances.
  - The student is familiar with Amazon S3 and knows how to use the primary functionalities of S3.
  - The student knows how to use the basic functionalities of SageMaker Autopilot to train Machine Learning models.

  Good

  - The student knows how to use SageMaker Autopilot to load data and create and configure experiments.
  - The student knows how to use SageMaker Autopilot to train models and deploy them to the AWS cloud.
  - The student knows how to use SageMaker Autopilot and job profiles to explore trained models, choose the best model, get inference from the model, and deploy it to the cloud.
  - The student knows how to use SageMaker Autopilot for tuning models’ hyperparameters.
  - The student knows the difference between SageMaker Studio notebooks and SageMaker Instance-based notebooks.
  - The student knows how to create Jupyter notebooks in SageMaker, attach EC2 compute instances to them, and run them on the cloud
  - The student knows how to connect to S3 from SageMaker notebooks.
  - The student is familiar with SageMaker Pipelines, its components, and use cases.
  - The student knows how to create simple pipelines using SageMaker Pipelines.

  Excellent

  - The knows how to use SageMaker Autopilot to do build and train supervised Machine Learning models with advanced hyperparameter tuning and performance evaluation
  - The knows how to use SageMaker Autopilot to do inference on SageMaker Console using endpoints
  - The student knows how to use SageMaker Python SDK to prepare training scripts, upload and insert libraries, and upload data on Jupyter instance.
  - The student knows how to use SageMaker Python SDK to load different datasets and perform data preprocessing and preparation.
  - The student knows how to use SageMaker Python SDK to build supervised Machine Learning models, train the models on training sets, deploy them to EC2 compute instances, and evaluate their performance.
  - The student knows how to use SageMaker Pipelines to create pipelines for processing data using different AWS services.
  - The student knows how to use SageMaker Pipelines to create pipelines with Machine Learning model training functionalities.
  - The student knows how to use SageMaker Pipelines for creating automatic pipelines for training, evaluating, and deploying Machine Learning and using them for prediction

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Lecture slides, tutorial videos, quizzes, exercises, project

  Planned learning activities and teaching methods

  This course is 100% virtual thanks to the comprehensive tutorial videos and content prepared for this course.
  
  Teaching methods
  - Tutorial Videos
  - Exercises
  - Quiz
  - Project
  - Self-study

  Assessment methods and criteria

  The student will pass this course after submitting the required quiz, assignments, and the final project.
  
  Evaluation methods
  Exercises 50%
  Quizzes 25%
  Project 25%

  Language of instruction

  English

  Timing

  01.08.2021 - 31.07.2022

  • 5 credits

  Group(s)

  • DiplomaMD

  Seats

  0 - 100

  Teacher(s)

  Virve Prami

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Lectures = 40h
  Exercises = 20h
  Self-study = 40h
  Quizzes = 5h
  Project = 35h
  Total = 140 hours

  Content periodicity

  Lectures = 40h
  Exercises = 20h
  Self-study = 40h
  Quizzes = 5h
  Project = 35h
  Total = 140 hours

  Location and Time

  100% online (self-study) course which can be done in own pace. Course environment is TechClass portal.

•     Administering a SQL Database Infrastructure TT00DD02-3007 01.01.2022-31.12.2022  6 credits  (ATX22TV) + -
  Learning outcomes of the course

  After taking Administering a SQL Database Infrastructure course, which prepares for 70-764 certification, student knows how-to configure data access and auditing, manage backup and restore of databases, manage and monitor SQL Server instances, manage high availability and disaster recovery.

  Course contents

  - Data Access and Auditing
  - Manage Backup and Restore Database;
  - Manage and Monitor SQL Server instances
  - Manage High Availability

  Assessment criteria

  Satisfactory

  Student knows how-to configure data access and auditing, manage backup and restore of databases, manage and monitor SQL Server instances, manage high availability and disaster recovery.with help from senior colleague.

  Good

  Student knows how-to configure data access and auditing, manage backup and restore of databases, manage and monitor SQL Server instances, manage high availability and disaster recovery with good level and work independently.

  Excellent

  Student knows how-to configure data access and auditing, manage backup and restore of databases, manage and monitor SQL Server instances, manage high availability and disaster recovery with excellent level and work independently. He/She also has ability to participate 70-764 certification exam.

  Further information

  Grading: Pass/Fail

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 6 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     Administering and Deploying System Center 2012 Configuration Manager, 70-243 TT00DC75-3007 01.01.2022-31.12.2022  5 credits  (ATX22TV) + -
  Learning outcomes of the course

  Get detailed instruction and hands-on practice planning and deploying Microsoft System Center 2012 R2 Configuration Manager and its associated site systems. This course is designed for IT Professionals who are responsible for designing and deploying one or more System Center 2012 R2 Configuration Manager sites and all supporting systems, as well as configuring and managing endpoints in those systems.
  
  You will learn how to plan for the deployment of the central administration site, one or more primary sites and secondary sites, and all associated site systems. You will also learn how to migrate from System Center 2012 Configuration Manager to System Center 2012 R2 Configuration Manager.
  
  This course will provide you with the necessary platform to gain hands on skills in Microsoft System Centre Configuration Manager 2012. By completing the lab tasks you will improve your practical skills in planning and designing System Centre Configuration Manager infrastructure, managing operating system deployment (OSD) deploying application and software updates, managing compliance settings, sites, clients, inventory, reports and queries.
  
  These same tasks will help you understand the objectives and competencies required by the Microsoft 70-243 certification exam.

  Course contents

  Get detailed instruction and hands-on practice planning and deploying Microsoft System Center 2012 R2 Configuration Manager and its associated site systems. This course is designed for IT Professionals who are responsible for designing and deploying one or more System Center 2012 R2 Configuration Manager sites and all supporting systems, as well as configuring and managing endpoints in those systems.
  
  You will learn how to plan for the deployment of the central administration site, one or more primary sites and secondary sites, and all associated site systems. You will also learn how to migrate from System Center 2012 Configuration Manager to System Center 2012 R2 Configuration Manager.
  
  This course will provide you with the necessary platform to gain hands on skills in Microsoft System Centre Configuration Manager 2012. By completing the lab tasks you will improve your practical skills in planning and designing System Centre Configuration Manager infrastructure, managing operating system deployment (OSD) deploying application and software updates, managing compliance settings, sites, clients, inventory, reports and queries.
  
  These same tasks will help you understand the objectives and competencies required by the Microsoft 70-243 certification exam.

  ---

  Mode of delivery

  Distance learning

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 500

  Teacher(s)

  Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

•     Administration Essentials for Salesforce TT00CC69-3008 01.01.2022-31.12.2022  8 credits  (ATX22TV) + -
  Learning outcomes of the course

  After the course, the student is able to:
  • Customize your application, including page layouts, fields, tabs, and business processes;
  • Create a secure Salesforce environment;
  • Maintain and import clean data;
  • Create high-value reports and dashboards;
  • Set up workflow automation.

  Course contents

  Getting Around the App, Understand the data model and navigation, Getting Your Organization Ready for Users, Manage user profiles, Manage record access with the role hierarchy, Work with record types and business processes, Create new reports with the report builder, Automate leads and cases Managing the Support Process.

  Assessment criteria

  Satisfactory

  Student is able to create a working Salesforce environment and maintain it with help from the senior colleague

  Good

  Student maintains Salesforce environment in good level, and can troubleshoot it

  Excellent

  Student maintains Salesforce environment in excellent level, and can work independently.

  Further information

  Virtualcourse

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in study environment.

  Planned learning activities and teaching methods

  100% Online Self-study course.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 8 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  8 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/ himself.

•     Advanced Powershell TT00EL09-3004 01.08.2021-31.12.2022  5 credits  (INSINÖÖRILIITTO) + -
  Learning outcomes of the course

  After completing the course, student is able to use powershell's advanced functions and properties.

  Course contents

  - Advanced functions
  - .NET ja REST API & Windows PowerShell
  - Controller Scripts
  - Debugging scripts
  - XML, JSON ja customized data format
  - Analyzing Powershell

  Assessment criteria

  Satisfactory

  Student knows with help how to write and interpret powershell script and he/she knows concept as a whole.

  Good

  Student is able to write and interpret powershell scripts with good level.

  Excellent

  Student is able to write and interpret powershell scripts with excellent leven and is able to apply his/her knowledge.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% Online Self-Study course.

  Assessment methods and criteria

  Can be find on study environment.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2022

  • 5 credits

  Group(s)

  • INSINÖÖRILIITTO

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     Advanced Powershell TT00EL09-3005 01.01.2022-31.12.2022  5 credits  (ATX22TV) + -
  Learning outcomes of the course

  After completing the course, student is able to use powershell's advanced functions and properties.

  Course contents

  - Advanced functions
  - .NET ja REST API & Windows PowerShell
  - Controller Scripts
  - Debugging scripts
  - XML, JSON ja customized data format
  - Analyzing Powershell

  Assessment criteria

  Satisfactory

  Student knows with help how to write and interpret powershell script and he/she knows concept as a whole.

  Good

  Student is able to write and interpret powershell scripts with good level.

  Excellent

  Student is able to write and interpret powershell scripts with excellent leven and is able to apply his/her knowledge.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% Online Self-Study course.

  Assessment methods and criteria

  Can be find on study environment.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLMENTS
  
  Open UAS Students via eform: https://elomake.metropolia.fi/lomakkeet/27116/lomake.html
  
  Metropolia's Degree Student
  Go to https://moodle.metropolia.fi/course/view.php?id=1528
  Enrolment key: powerijatko

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     Advanced Routing and Switching in Modern Enterprise Networks TX00EV25-3001 23.08.2021-19.12.2021  10 credits  (ICT19-SI-N) + -
  Learning outcomes of the course

  After completing the course, the students know operations and design principles of modern fault-tolerant enterprise networks and can also implement and manage those networks. Students will understand purposes and characteristics of software-defined and programmable networks.

  Prerequisites and co-requisites

  Basics of computer networks

  Course contents

  - Switching technologies
  - Configure L2 redundancy in an enterprise network
  - Multilayer switching
  - OSPF, EIGRP and BGP in Enterprise networks
  - QOS and multicast
  - Secure and scalable enterprise WLAN networks
  - Site-to-site and remote-access VPN
  - Security in enterprise networks
  - Working with devices from multiple vendors

  Assessment criteria

  Satisfactory

  Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development.

  Good

  Students have achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Students are able to define the course concepts and models and are able to justify the analysis. The student is able to apply their knowledge in leisure, study and work situations. The student understands the importance of expertise in the field of network technology and is able to analyze his/her own expertise.

  Excellent

  Students have achieved the objectives of the course with excellent marks. Students master commendably the course subject area’s concepts and models. Students are able to make justified and fluent analysis and to present concrete development measures. The students are well prepared to apply their knowledge in leisure, study and work situations. Students are able to analyze the network technology sector expertise and the evolvement of their own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 10 credits

  Group(s)

  • ICT19-SI-N

  Seats

  0 - 40

  Teacher(s)

  Marko Uusitalo

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Advanced Usage of Office Programs TT00CJ90-3009 01.01.2022-31.07.2023  6 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After the course the student is able to use Office products to increase her/his productivity.

  Course contents

  Products to learn:
  - Word
  - Excel
  - Access
  - Powerpoint

  Assessment criteria

  Satisfactory

  User Interface:
  - the student understands every office program's user interface and is able to optimize it with the
  instructor's help;
  
  Basic Functions:
  - the student is able to do basic operations with every office program with the instructor's help;
  
  Advanced functions:
  - the student is able to write simple macro programs and automate operations with office programs with the instructor's help;
  
  Joint operation with other office programs:
  - the student is able to create office documents which benefit other office programs, with the instructor's help;

  Good

  User Interface:
  - the student understands every office program's user interface and is able to optimize it;
  - the student shows independent solutions.
  
  Basic Functions:
  - the student is able to do basic operations with every office program;
  - the student shows independent solutions.
  
  Advanced functions:
  - the student is able to write relatively complex macro programs and automate operations with office programs;
  - the student shows independent solutions.
  
  Joint operation with other office programs:
  - the student is able to create office documents which benefit other office programs;
  - the student shows independent solutions.

  Excellent

  User Interface:
  - the student understands every office program's user interface and is able to optimize it;
  - the student shows independent solutions and critical evaluation.
  
  Basic Functions:
  - the student is able to do basic operations with every office program;
  - the student shows independent solutions and critical evaluation.
  
  Advanced functions:
  - the student is able to write relatively complex macro programs and automate operations with office programs;
  - the student shows independent solutions and critical evaluation.
  
  Joint operation with other office programs:
  - the student is able to create office documents which benefit other office programs;
  - the student shows independent solutions and critical evaluation.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in LabSim environment.

  Planned learning activities and teaching methods

  100% online Self-study course. All you need is web browser and working network connection.
  
  You have two choices for completion. You can do couple of exercises from each module, and or you can do the test. This test can be found from the environment.

  Assessment methods and criteria

  You have two choices for completion. You can do couple of exercises from each module, and or you can do the test. This test can be found from the environment.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.07.2023

  • 6 credits

  Group(s)

  • ATX22TV
  • ATX23TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  You have two choices for completion. You can do couple of exercises from each module, and or you can do the test. This test can be found from the environment.

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via LabSim -environment and timetable is totally up to student. Course can be done in own pace.

•     Agile Project Management TX00EU13-3002 24.08.2021-14.10.2021  3 credits + -
  Learning outcomes of the course

  On completion of the course, the student is familiar with the main project management philosophies like waterfall model and agile methodology and their background. Students understand SW version control practices, continuous integration and test automation role in agile project management in SW development and IT sector. Student knows some used agile methodologies and their role in SW project management.

  Prerequisites and co-requisites

  -

  Course contents

  - Project management key aspects and process
  - Fundamentals of project management models
  - Waterfall model and agile development
  - Different agile development methods introduction and exercising as SW project management practices
  - Version and configuration management, continuous integration and automated testing as part of project management

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Name of lecturer(s)

  Matti Oosi

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  24.08.2021 - 14.10.2021

  Enrollment date

  29.06.2021 - 22.08.2021

  • 3 credits

  Seats

  0 - 20

  Teacher(s)

  Matti Oosi

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  Hyväksytty/Hylätty

•     Amazon Cloud Foundation TX00DW03-3002 23.08.2021-17.10.2021  5 credits  (TXK21S2) + -
  Learning outcomes of the course

  Amazon Cloud Foundation is an AWS Academy curriculum designed to help students develop technical expertise in cloud computing. Upon a successful completion of the course, participants will know the basics of cloud computing, can identify global infrastructure components of cloud computing and knows the basics of implementation and architecture of public cloud computing.

  Prerequisites and co-requisites

  Basic understanding of ict and networking technology

  Course contents

  Cloud computing concepts
  Overview of AWS global infrastructure
  AWS core services
  Basics of cloud architecture
  Automatic Scaling and Monitoring

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Recommended or required reading

  AWS Academy course material

  Planned learning activities and teaching methods

  lecture
  laboratory exercises
  theory exercies

  Assessment methods and criteria

  learning assignments
  theory exam

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TXK21S2

  Seats

  0 - 60

  Teacher(s)

  Erik Pätynen

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

  Completion alternatives

  AWS Cloud Practitioner certificate and project work
  
  AWS Solutions Architect - Associate certificate and project work
  
  AWS Solutions Architect - Professional certificate and project work

  Work placement(s)

  AWS Academy

  Location and Time

  distance learning

•     Amazon Web Services TX00ED10-3002 10.01.2022-08.05.2022  5 credits  (TXK21S2) + -
  Learning outcomes of the course

  AWS – Cloud Computing Architecture is an AWS Academy curriculum designed to help students develop technical expertise in cloud computing and prepare them for the AWS Certified Solutions Architect – Associate certification exam.
  Upon a successful completion of the course, participants will know the value, benefits of cloud computing, the financial advantages on AWS, the core components and services of cloud computing on AWS, scaling infrastructure on AWS, Cloud migration as well as high availability and business continuity. After completing this course the learner knows design patterns of AWS cloud and can apply them to architectural designs solutions.

  Prerequisites and co-requisites

  Amazon Cloud Foundation or basic knowledge about cloud computing

  Course contents

  Introduction Cloud Computing Architure and AWS design
  AWS core infrastructure components, services and Management tools
  Designing highly available environment on AWS
  Automation and decoupling your Infrastructure
  Well architected framework
  Troubleshooting
  Design patterns and sample architectures

  Assessment criteria

  Satisfactory

  Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development.

  Good

  Students have achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Students are able to define the course concepts and models and are able to justify the analysis. The student is able to apply their knowledge in study and work
  situations. The student understands the importance of expertise in the field of information technology and is able to analyze his/her own expertise.

  Excellent

  Students have achieved the objectives of the course with excellent marks. Students master commendably the course subject area’s concepts and models. Students are able to make justified and fluent analysis and to present concrete development measures. The students are well prepared to apply their knowledge in study and work situations. Students are able to analyze the information technology sector expertise and the evolvement of their own expertise.

  ---

  Mode of delivery

  Face-to-face

  Recommended or required reading

  AWS Academy course material

  Planned learning activities and teaching methods

  lectures
  laboratory exercises
  theory exercises

  Assessment methods and criteria

  learning assignments
  theory exam

  Language of instruction

  English

  Timing

  10.01.2022 - 08.05.2022

  Enrollment date

  29.11.2021 - 09.01.2021

  • 5 credits

  Group(s)

  • TXK21S2

  Seats

  0 - 60

  Teacher(s)

  Erik Pätynen

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

  Completion alternatives

  AWS Solutions Architect - Associate certificate and project work
  
  AWS Solutions Architect - Professional certificate and project work

  Work placement(s)

  AWS academy

•     Android Programming TX00CR64-3009 25.10.2021-19.12.2021  5 credits  (TVT19K-O) + -
  Learning outcomes of the course

  On completion of the course the student has knowledge of the Android platform architecture and the most relevant mechanisms employed in the application development. The student has the needed know-how to implement interactive applications as well as services utilizing standard design patterns.
  The student knows how to integrate location information and sensor data with the application.

  Prerequisites and co-requisites

  Java-ohjelmointitaidot (not translated)

  Course contents

  - Application components and resources
  - User interface structure and event handling, customizing and combining user interface elements
  - Adapters and adapter views, menu structures
  - Persisting data, file IO, database
  - Network operations and threads
  - Services, content providers and broadcast events
  - Widgets
  - Location information and sensor data

  Further information

  Tieto- ja viestintätekniikan tutkinto-ohjelman valinnainen opintojakso. (not translated)

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  24.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT19K-O

  Seats

  0 - 36

  Teacher(s)

  Juha Kämäri

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Applied Anatomy and Physiology TX00CG23-3009 23.08.2021-17.10.2021  5 credits  (TVT20-H) + -
  Learning outcomes of the course

  After completing the course, the student knows phenomena measured from human body and their utilization opportunities, understands interaction between a human body and functionality behind measurement results, and applies learned knowledge.

  Course contents

  • Basic structure and functions of musculoskeletal system
  • Structure and functions of cardiovascular system
  • Structure and functions of respiratory system
  • Basic functions of nervous system and sensory system
  • Practical measurements and analysis

  Assessment criteria

  Satisfactory

  Student has basic knowledge of phenomena measured from a human body and measurement utilization opportunities, and uses learned knowledge.

  Good

  Student knows phenomena measured from a human body and measurement utilization opportunities, and applies learned knowledge.

  Excellent

  Student thoroughly knows phenomena measured from a human body and measurement utilization opportunities, and applies learned knowledge in advanced manner.

  ---

  Mode of delivery

  Face-to-face

  Recommended or required reading

  Sand, O. ym.: Ihminen Fysiologia ja anatomia. WSOYpro or Bjålie, J.G. ym.: Ihminen Fysiologia ja anatomia. WSOY or Leppäluoto J. ym: Anatomia ja fysiologia. Rakenteesta toimintaan. WSOYpro. or Nienstedt, W. ym. Ihmisen fysiologia ja anatomia. WSOY

  Planned learning activities and teaching methods

  Interactive lecture
  Guided assigments

  Assessment methods and criteria

  Exam
  Reports

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  01.01.2020 - 01.01.2020

  • 5 credits

  Group(s)

  • TVT20-H

  Seats

  0 - 40

  Teacher(s)

  Anu Valtonen, Pirkko-Leena Kuosa

  Further information for students

  N/A

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

  Completion alternatives

  Erityisen tuen päätökset: Mikäli opiskelijalla on erityisen tuen päätös, joka vaikuttaa opintojakson suorittamiseen, tulee opiskelijan olla yhteydessä opintojaksototeutuksen vastuuopettajaan heti ilmoittautumisajan päätyttyä. (not translated)

  Exam schedule

  Exam:
  1) 16.9.2021
  2) 14.10.2021

  Students use of time and load

  N/A

•     Artificial Intelligence in Business Management TX00EL42-3002 02.08.2021-06.08.2021  3 credits  (ICTSUMMER) + -
  Learning outcomes of the course

  At the end of this introductory course, students will be better informed about the increasing role of AI in business management and their lives. This course will motivate students to examine their life and work aspirations as AI is displacing many jobs and will continue to do so. At the end of this course, students will be able to
  - Explain what artificial intelligence is and what is the role it is playing in our lives,
  - Appreciate the impact AI is making in various industries from health to manufacturing,
  - Reflect on the pros and cons of AI and start a dialogue on how to mitigate possible negatives,
  - Form an opinion on the ethical component of AI,
  - Comment on how European Union and the world should scale up AI initiatives,
  - Give better informed commentary on the increasing role of AI in business world and our lives,
  - Acquire motivation to examine our life and work aspirations as AI is displacing many jobs and will continue to do so,
  - Demonstrate better understanding of the skills which would be required in the future of work and plan accordingly.

  Prerequisites and co-requisites

  No prerequisite

  Course contents

  Technologies have changed the way we live, work and play. One of such technology which is making huge impacts is Artificial Intelligence.This introductory course will sensitise participants to the advancing role of AI in various industries. The advantages of AI will be discussed together with areas to be careful about. The inclusion of this course is timely as European Union is deliberating on the role of ethics and trusting AI.

  Assessment criteria

  Satisfactory

  - Students’ active attendance (3 classes)
  - Students’ active participation in class discussions (3 classes)
  - Students’ submission of exercises (3 classes)

  Good

  - Students’ active attendance (4 classes)
  - Students’ active participation in class discussions (4 classes)
  - Students’ submission of exercises (4 classes)

  Excellent

  - Students’ active attendance (5 classes)
  - Students’ active participation in class discussions (5 classes)
  - Students’ submission of exercises (5 classes)

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Course website: http://tashfeen.pbworks.com
  All learning material is available on the course website.

  Planned learning activities and teaching methods

  Teaching methods include:
  - Lectures
  - Videos
  - Discussions
  - Case Analysis

  Assessment methods and criteria

  The course assessment is based on
  - Active attendance
  - Active participation in class discussions
  - Submission of assignments

  Language of instruction

  English

  Timing

  02.08.2021 - 06.08.2021

  Enrollment date

  03.05.2021 - 31.07.2021

  • 3 credits

  Group(s)

  • ICTSUMMER

  Seats

  0 - 80

  Teacher(s)

  Tashfeen Ahmad

  Further information for students

  Course website: http://tashfeen.pbworks.com
  Please feel free to contact the lecturer via email: mrtashfeen@hotmail.com

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  0-5

  Location and Time

  02.08.2021 - 06.08.2021 (evenings 18:00-21:00)

•     Artificial intelligence with Python TT00EV76-3002 15.09.2021-31.12.2021  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence using Python Programming Language in practise.

  Course contents

  - Python Quick Recap
  - Python Arrays, Tables, Vectors, Matrices
  - AI: Short Description
  - AI: Regression 1
  - AI: Regression 2
  - AI: Classification 1
  - AI: Classification 2
  - AI: Miscellanae

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  After student has done at least 80% of tasks he/she can get grade pass.

  Language of instruction

  English

  Timing

  15.09.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  None.

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Course can be done in own pace. So, the timetable is up to student her-/himself.

  Content periodicity

  Course can be done in own pace. So, student can schedule her/his studies her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Artificial intelligence with Python TT00EV76-3003 17.06.2022-31.12.2022  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence using Python Programming Language in practise.

  Course contents

  - Python Quick Recap
  - Python Arrays, Tables, Vectors, Matrices
  - AI: Short Description
  - AI: Regression 1
  - AI: Regression 2
  - AI: Classification 1
  - AI: Classification 2
  - AI: Miscellanae

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  After student has done at least 80% of tasks he/she can get grade pass.

  Language of instruction

  English

  Timing

  17.06.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  None.

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Course can be done in own pace. So, the timetable is up to student her-/himself.

  Content periodicity

  Course can be done in own pace. So, student can schedule her/his studies her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Artificial intelligence with Python TT00EV76-3004 01.01.2022-14.09.2022  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence using Python Programming Language in practise.

  Course contents

  - Python Quick Recap
  - Python Arrays, Tables, Vectors, Matrices
  - AI: Short Description
  - AI: Regression 1
  - AI: Regression 2
  - AI: Classification 1
  - AI: Classification 2
  - AI: Miscellanae

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  After student has done at least 80% of tasks he/she can get grade pass.

  Language of instruction

  English

  Timing

  01.01.2022 - 14.09.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  None.

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Course can be done in own pace. So, the timetable is up to student her-/himself.

  Content periodicity

  Course can be done in own pace. So, student can schedule her/his studies her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Artificial intelligence with Python TT00EV76-3006 01.01.2022-31.12.2022  3 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence using Python Programming Language in practise.

  Course contents

  - Python Quick Recap
  - Python Arrays, Tables, Vectors, Matrices
  - AI: Short Description
  - AI: Regression 1
  - AI: Regression 2
  - AI: Classification 1
  - AI: Classification 2
  - AI: Miscellanae

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  After student has done at least 80% of tasks he/she can get grade pass.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  None.

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Course can be done in own pace. So, the timetable is up to student her-/himself.

  Content periodicity

  Course can be done in own pace. So, student can schedule her/his studies her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Artificial intelligence with Python TT00EV76-3007 15.09.2021-31.12.2025  3 credits  (Polkuopinnot_NonStop, ...) + -
  Learning outcomes of the course

  After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence using Python Programming Language in practise.

  Course contents

  - Python Quick Recap
  - Python Arrays, Tables, Vectors, Matrices
  - AI: Short Description
  - AI: Regression 1
  - AI: Regression 2
  - AI: Classification 1
  - AI: Classification 2
  - AI: Miscellanae

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  After student has done at least 80% of tasks he/she can get grade pass.

  Language of instruction

  English

  Timing

  15.09.2021 - 31.12.2025

  • 3 credits

  Group(s)

  • Polkuopinnot_NonStop
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  None.

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Course can be done in own pace. So, the timetable is up to student her-/himself.

  Content periodicity

  Course can be done in own pace. So, student can schedule her/his studies her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Automated Software Testing with Selenium TT00EM53-3003 01.01.2022-31.12.2022  5 credits  (ATX22TV) + -
  Learning outcomes of the course

  This course aims to acquaint you with Selenium, which is an open-source web-based automation tool, from both practical and theoretical approach step-by-step. Generally accepted that automation testing occupies center stage in Quality Assurance since it can act as a catalyst for testers to achieve a desirable quality. There are various automation testing tools, of particular note is Selenium owing to several reasons. This course starts with fundamental Selenium concepts and will gradually move to advance topics like different commands, Action classes, and framework creation. This course is suitable for beginners with little or no automation experience to an advanced level. At the end of the course, students are expected to appropriately gain the knowledge of automation concepts and automate the considerable part of test cases with the TestNG framework.
  
  This course is 100% virtual thanks to the comprehensive interactive material and content prepared for this course.
  
  The student will pass this course after submitting the required quiz and assignments.

  Course contents

  1. Selenium Introduction:
  What is Selenium? - Selenium IDE - Selenium RC - Selenium Webdriver - Selenium Grid - Who developed Selenium?
  
  2. Selenium WebDriver Setup:
  Introduction - Install Java - Install Eclipse IDE - Install Selenium WebDriver - Configure Eclipse IDE - First Selenium WebDriver Script
  
  3. Locators in Selenium WebDriver:
  What are Locators? - Locating by ID - Locating by Name - Locating by Class Name - Locating by Tag Name - Locating by Link Text & Partial Link Text - Locating by CSS Selector - Locating by XPath
  
  4. Commands in Selenium WebDriver:
  Browser Commands - Navigation Commands - WebElement Commands - Operational Methods - Verification Methods - Data Capture Methods - CheckBox and Radio Buttons - DropDown & Multiple Select -
  
  5. Switching alert & windows:
  Wait statements - Handling Alert - Handling Multiple Windows - Handling iframe
  
  6. Action Class:
  Actions class - Right Click and Double Click - Drag and Drop - Mouse Hover - ToolTip - Keyboard Events
  
  7. Tips & Tricks
  Headless Browser Testing - Take Screenshot - Upload and Download a file - Find Broken Links
  
  8. TestNG Framework
  Introduction to TestNG - TestNG Installation in Eclipse - First Test Case with TestNG - TestNG Test Suite - TestNG Annotations - TestNG Assertions - TestNG Groups - TestNG Dependency - TestNG Priority - TestNG Data Provider - Cross-browser and Parallel Testing – TestNG Listeners

  Assessment criteria

  Satisfactory

  - The student knows the basic definitions of Selenium.
  - The student knows the difference between Selenium IDE, Selenium RC, Grid, and WebDriver.
  - The student knows how to set up the Selenium web driver.
  - The student knows how to configure the IDE.

  Good

  - The student can locate elements within the website through a different approach.
  - The student can fetch data.
  - The student can clear inputs.
  - The student can navigate in browsers.
  - The student can verify elements.
  - The student can handle alerts.
  - The student can move between multiple windows.
  - The student can perform click events.

  Excellent

  - The student can handle mouse & keyboard events.
  - The student can take a screenshot.
  - The student knows what headless browsers are and run to test the application with the help of them.
  - The student knows how to download and upload a file.
  - The student knows what TestNG is.
  - The student knows how to use Annotations, Groups, and Dependency.
  - The student knows how to use the data provider option in TestNG.
  - The student knows how to perform Parallel Testing.
  - The student knows how to implement Listeners.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in TechClass -portal.

  Planned learning activities and teaching methods

  This course is 100% virtual thanks to the comprehensive interactive material and content prepared for this course.
  
  Course includes:
  - Assignments
  - Quiz
  - Projects
  - Self-study

  Assessment methods and criteria

  The student will pass this course after submitting the required quiz and assignments.
  
  Exercises 30%
  Quizzes 20%
  Project 40%
  Essay 10%

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online in TechClass -portal.

  International connections

  N/A

  Students use of time and load

  Lectures = 40h
  Assignments = 25h
  Self-study = 40h
  Quiz = 5h
  Project = 20h
  Essay = 5h
  Total = 135 hours

  Location and Time

  Course is 100% online in TechClass -portal and course can be done in own pace.

•     Azure Machine Learning TT00EO92-3003 01.01.2022-31.12.2022  15 credits  (ATX22TV) + -
  Learning outcomes of the course

  Azure Machine Learning (ML) is Microsoft’s cloud-based service for machine learning implementations, which runs on top of Microsoft Azure cloud and allows for building, deploying, tracking machine learning and deep learning models with lots of capabilities and customizations. This course introduces the primary machine learning tools available on the Azure ML studio and focuses on standardized approaches to data analytics and machine learning implementation (e.g., predictive modeling) based on them. After passing this course, the student will learn to build, train, deploy, automate, manage, and track enterprise-grade machine learning models from scratch in a simplified way using powerful Azure workspaces.
  This course is 100% virtual thanks to the comprehensive tutorial videos and content prepared for this course.
  The student will pass this course after submitting required quiz, assignments, and the final project.

  Course contents

  1. Introduction:
  Basics of Machine Learning – Importance of Data – Types of Machine Learning – Machine Learning Pipeline – Machine Learning Implementation – Why Cloud-based Services? – Microsoft Azure Cloud Services
  2. Azure Machine Learning:
  What is Azure ML? – Getting Started with Azure ML – What is Azure ML Studio? – Azure ML Architecture and Concepts – Compute Targets
  3. Azure Machine Learning Designer–Working with Data:
  Introduction to Azure ML Designer – Create a New Pipeline – Import Data: Manual Data Entry and Sample Datasets – Import Data: Create a Dataset – Visualize the Data – Prepare Data: Select Columns – Prepare Data: Clean Missing Data – Prepare Data: Apply Math Operations – Prepare Data: Split Data
  4. Azure Machine Learning Designer–Training and Deployment:
  Add Training Modules – Add Evaluation Modules – Set the Default Compute Target – Submit the Pipeline – View Evaluation Results – Create a Real-time Inference Pipeline – Create an Inferencing Cluster – Deploy the Real-time Endpoint – Test the Real-time Endpoint – Clean-up Resources – Algorithm Cheat Sheet for Azure ML Designer
  5. Automated Machine Learning:
  Introduction to Automated ML – Getting Started with Automated ML – Create and Load a Dataset – Configure Experiment Run – Explore Models – Deploy the Best Model – Prevent Overfitting with Automated ML – Example: Time-Series Forecasting Model
  5. Azure Machine Learning Python SDK:
  Getting Started with Azure ML in Jupyter Notebooks – Create, Run, and Manage Notebooks – Azure ML Python SDK – Setup Local Computer – Train a Model – Prepare Your Code for Production – Deploy the Model – Automated ML with Python SDK
  6. Azure Event Grid:
  What is Event Grid? – Event Model and Types – Create Event-driven Workflows – Example 1: Send Email Alerts – Example 2: Data Drift Triggers Retraining
  7. What’s More?
  Connect to Azure Storage Services – Git Integration for Azure ML – Plan and Manage Costs for Azure ML – Next Steps

  Assessment criteria

  Satisfactory

  - The student is familiar with the cloud-based service.
  - The student is familiar with about Azure Machine Learning Studio.
  - The student knows about how to use Azure Machine Learning Designer service.
  - The student is familiar how to train a model using Azure Machine Learning Designer.
  - The student is familiar with concept of Automated Machine Learning service in AML.
  - The student is familiar with different compute resource in AML.

  Good

  - The student knows how to use Automated Machine Learning Service to implement and deploy different machine learning models.
  - The student knows the how to use Jupyter notebook and run and manage it.
  - The student is familiar with different assets in Azure Machine Learning Studio.
  - The student is familiar with Azure Machine Learning SDK.
  - The student knows how to setup his/her local computer.
  - The student knows how to use Azure machine learning compute resource to train his/her models.
  - The student is familiar with the concept of Experiment.
  - The student is familiar with the concept of Event Grid.

  Excellent

  - The student knows how to create an environment for his/her model.
  - The student can prepare his/her code for deploying different machine learning models.
  - The student can understand the technical document of Azure Machine learning Services.
  - The student is familiar with Microsoft cognitive service.
  - The student knows how transfer learning models work.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Lecture slides
  Tutorial videos
  Quizzes
  Exercises
  Project

  Planned learning activities and teaching methods

  100% online Self-Study course.
  
  - Tutorial Videos
  - Exercises
  - Quiz
  - Project
  - Self-study

  Assessment methods and criteria

  Exercises 50%
  Quizzes 25%
  Project 25%

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 15 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  15 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Lectures = 85h
  Exercises = 95h
  Self-study = 100h
  Quizzes = 15h
  Project = 65h
  Total = 360 hours

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course can be done with own pace in TechClass environment.

•     Azure Machine Learning TT00EV89-3001 01.08.2021-31.07.2022  5 credits  (DiplomaMD) + -
  Learning outcomes of the course

  Azure Machine Learning (ML) is Microsoft’s cloud-based service for machine learning implementations, which runs on top of Microsoft Azure cloud and allows for building, deploying, tracking machine learning and deep learning models with lots of capabilities and customizations. This course introduces the primary machine learning tools available on the Azure ML studio and focuses on standardized approaches to data analytics and machine learning implementation (e.g., predictive modeling) based on them. By the end of this course, the student will learn to build, train, deploy, automate, manage, and track enterprise-grade machine learning models from scratch in a simplified way using powerful Azure workspaces.

  Course contents

  1. Introduction:
  Basics of Machine Learning – Importance of Data – Types of Machine Learning – Machine Learning Pipeline – Machine Learning Implementation – Why Cloud-based Services? – Microsoft Azure Cloud Services
  
  2. Azure Machine Learning:
  What is Azure ML? – Getting Started with Azure ML – What is Azure ML Studio? – Azure ML Architecture and Concepts – Compute Targets
  
  3. Azure Machine Learning Designer–Working with Data:
  Introduction to Azure ML Designer – Create a New Pipeline – Import Data: Manual Data Entry and Sample Datasets – Import Data: Create a Dataset – Visualize the Data – Prepare Data: Select Columns – Prepare Data: Clean Missing Data – Prepare Data: Apply Math Operations – Prepare Data: Split Data
  
  4. Azure Machine Learning Designer–Training and Deployment:
  Add Training Modules – Add Evaluation Modules – Set the Default Compute Target – Submit the Pipeline – View Evaluation Results – Create a Real-time Inference Pipeline – Create an Inferencing Cluster – Deploy the Real-time Endpoint – Test the Real-time Endpoint – Clean-up Resources – Algorithm Cheat Sheet for Azure ML Designer
  
  5. Automated Machine Learning:
  Introduction to Automated ML – Getting Started with Automated ML – Create and Load a Dataset – Configure Experiment Run – Explore Models – Deploy the Best Model – Prevent Overfitting with Automated ML – Example: Time-Series Forecasting Model
  
  5. Azure Machine Learning Python SDK:
  Getting Started with Azure ML in Jupyter Notebooks – Create, Run, and Manage Notebooks – Azure ML Python SDK – Setup Local Computer – Train a Model – Prepare Your Code for Production – Deploy the Model – Automated ML with Python SDK
  
  6. Azure Event Grid:
  What is Event Grid? – Event Model and Types – Create Event-driven Workflows – Example 1: Send Email Alerts – Example 2: Data Drift Triggers Retraining
  
  7. What’s More?
  Connect to Azure Storage Services – Git Integration for Azure ML – Plan and Manage Costs for Azure ML – Next Steps

  Assessment criteria

  Satisfactory

  - The student is familiar with the cloud-based service.
  - The student is familiar with about Azure Machine Learning Studio.
  - The student knows about how to use Azure Machine Learning Designer service.
  - The student is familiar how to train a model using Azure Machine Learning Designer.
  - The student is familiar with concept of Automated Machine Learning service in AML.
  - The student is familiar with different compute resource in AML.

  Good

  - The student knows how to use Automated Machine Learning Service to implement and deploy different machine learning models.
  - The student knows the how to use Jupyter notebook and run and manage it.
  - The student is familiar with different assets in Azure Machine Learning Studio.
  - The student is familiar with Azure Machine Learning SDK.
  - The student knows how to setup his/her local computer.
  - The student knows how to use Azure machine learning compute resource to train his/her models.
  - The student is familiar with the concept of Experiment.
  - The student is familiar with the concept of Event Grid.

  Excellent

  - The student knows how to create an environment for his/her model.
  - The student can prepare his/her code for deploying different machine learning models.
  - The student can understand the technical document of Azure Machine learning Services.
  - The student is familiar with Microsoft cognitive service.
  - The student knows how transfer learning models work.

  Further information

  Course is for Diploma in Machine & Deep Learning Students.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Lecture slides, tutorial videos, quizzes, exercises, project

  Planned learning activities and teaching methods

  This course is 100% virtual thanks to the comprehensive tutorial videos and content prepared for this course.
  
  The student will pass this course after submitting required quiz, assignments, and the final project

  Assessment methods and criteria

  Exercises 50%
  Quizzes 25%
  Project 25%

  Language of instruction

  English

  Timing

  01.08.2021 - 31.07.2022

  • 5 credits

  Group(s)

  • DiplomaMD

  Seats

  0 - 100

  Teacher(s)

  Virve Prami

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Lectures = 40h
  Exercises = 20h
  Self-study = 40h
  Quizzes = 5h
  Project = 35h
  Total = 140 hours

  Location and Time

  Course is 100% online (Self-Study) course and study environment is TechClass portal.

•     Basic Concepts of Web Technology TX00CD47-3009 25.10.2021-19.12.2021  15 credits  (ICT20-M) + -
  Learning outcomes of the course

  This course will provide understanding of how web technologies and databases can be used in building backend and mobile front end services.

  Prerequisites and co-requisites

  N/A

  Course contents

  • Java EE basics or Node.js basics
  • Database design and management
  • Usability concepts
  • Front end development

  Assessment criteria

  Satisfactory

  Capability to develop basic web service including back end and front end components.

  Good

  Good understanding of relevant web technologies and capability to apply them in developing web service including back end and front end components. Understanding of basic usability criteria in UI and interaction logic.

  Excellent

  Very good understanding of relevant web technologies and capability to apply them in developing web service including back end and front end components. Application of basic usability criteria in UI and interaction logic.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  01.01.2020 - 01.01.2020

  • 15 credits

  Group(s)

  • ICT20-M

  Seats

  0 - 40

  Teacher(s)

  Ilkka Kylmäniemi, Patrick Ausderau, Ulla Sederlöf, Aarne Klemetti, Birgitta Nenonen-Andersson

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Basic Excel 365 TT00EW23-3001 01.08.2021-31.12.2021  3 credits  (ATX21TV) + -
  Learning outcomes of the course

  The course will get acquainted with the use of Excel spreadsheet software. The goal is to give a full picture of the foundations of the spreadsheet and use of the Excel program.
  
  The course goes through e.g. worksheet processing, creating formulas, linking tables, creation of diagrams and design of the sheet.
  
  The course has been prepared for Excel 365 and Excel 2019 versions. Instructions are also suitable for browser-based Excel and for earlier versions of Excel.
  
  The course is also suitable for contra-starters.

  Course contents

  The course is formed from 12 lessons, which contains theory and practical exercises.
  
  Before lessons will be presented spreadsheet activity using a simple example.

  Further information

  Practical examples and exercises are done at the student's own workstation.
  
  Free Month Trial of Office 365, containing Excel 365 software can be downloaded from Microsoft.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in study environment.

  Planned learning activities and teaching methods

  Course is 100% online (self-study) course which can be done in own pace.
  
  The course is formed from 12 lessons and Final exam (online). Lessons contains theory and practical exercises. Lessons are conducted in order.
  
  Note that the lessons can include several pages. The link to the next page is at the end of the previous page. There's an end-of-lesson link on the last page.

  Assessment methods and criteria

  The course receives an accepted entry after all the 12 lessons of the course and Final Test has been done approved.
  
  The final exam has ? 50 multiple choice tasks and has a duration of 150 minutes.
  
  The lowest approval score is 700/1000. If the result falls below it, the test must be renewed. Final exam can be renewed 3 times!

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • ATX21TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLMETS
  
  Metropolia's Degree Students
  Go to Moodle -> https://moodle.metropolia.fi/course/view.php?id=4075
  Enrolment key: Eskeli

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Content periodicity

  The course is formed from 12 lessons and Final exam. Lessons contains theory and practical exercises. Lessons are conducted in order.

  Location and Time

  Course environment is Metropolia's Moodle and course can be done in own pace.

•     Basic Excel 365 TT00EW23-3002 01.01.2022-31.12.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  The course will get acquainted with the use of Excel spreadsheet software. The goal is to give a full picture of the foundations of the spreadsheet and use of the Excel program.
  
  The course goes through e.g. worksheet processing, creating formulas, linking tables, creation of diagrams and design of the sheet.
  
  The course has been prepared for Excel 365 and Excel 2019 versions. Instructions are also suitable for browser-based Excel and for earlier versions of Excel.
  
  The course is also suitable for contra-starters.

  Course contents

  The course is formed from 12 lessons, which contains theory and practical exercises.
  
  Before lessons will be presented spreadsheet activity using a simple example.

  Further information

  Practical examples and exercises are done at the student's own workstation.
  
  Free Month Trial of Office 365, containing Excel 365 software can be downloaded from Microsoft.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in study environment.

  Planned learning activities and teaching methods

  Course is 100% online (self-study) course which can be done in own pace.
  
  The course is formed from 12 lessons and Final exam (online). Lessons contains theory and practical exercises. Lessons are conducted in order.
  
  Note that the lessons can include several pages. The link to the next page is at the end of the previous page. There's an end-of-lesson link on the last page.

  Assessment methods and criteria

  The course receives an accepted entry after all the 12 lessons of the course and Final Test has been done approved.
  
  The final exam has ? 50 multiple choice tasks and has a duration of 150 minutes.
  
  The lowest approval score is 700/1000. If the result falls below it, the test must be renewed. Final exam can be renewed 3 times!

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLMETS
  
  Metropolia's Degree Students
  Go to Moodle -> https://moodle.metropolia.fi/course/view.php?id=4075
  Enrolment key: Eskeli

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Content periodicity

  The course is formed from 12 lessons and Final exam. Lessons contains theory and practical exercises. Lessons are conducted in order.

  Location and Time

  Course environment is Metropolia's Moodle and course can be done in own pace.

•     Basic Excel 365 TT00EW23-3003 01.01.2022-30.04.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  The course will get acquainted with the use of Excel spreadsheet software. The goal is to give a full picture of the foundations of the spreadsheet and use of the Excel program.
  
  The course goes through e.g. worksheet processing, creating formulas, linking tables, creation of diagrams and design of the sheet.
  
  The course has been prepared for Excel 365 and Excel 2019 versions. Instructions are also suitable for browser-based Excel and for earlier versions of Excel.
  
  The course is also suitable for contra-starters.

  Course contents

  The course is formed from 12 lessons, which contains theory and practical exercises.
  
  Before lessons will be presented spreadsheet activity using a simple example.

  Further information

  Practical examples and exercises are done at the student's own workstation.
  
  Free Month Trial of Office 365, containing Excel 365 software can be downloaded from Microsoft.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in study environment.

  Planned learning activities and teaching methods

  Course is 100% online (self-study) course which can be done in own pace.
  
  The course is formed from 12 lessons and Final exam (online). Lessons contains theory and practical exercises. Lessons are conducted in order.
  
  Note that the lessons can include several pages. The link to the next page is at the end of the previous page. There's an end-of-lesson link on the last page.

  Assessment methods and criteria

  The course receives an accepted entry after all the 12 lessons of the course and Final Test has been done approved.
  
  The final exam has ? 50 multiple choice tasks and has a duration of 150 minutes.
  
  The lowest approval score is 700/1000. If the result falls below it, the test must be renewed. Final exam can be renewed 3 times!

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 30.04.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLMETS
  
  Metropolia's Degree Students
  Go to Moodle -> https://moodle.metropolia.fi/course/view.php?id=4075
  Enrolment key: Eskeli

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Content periodicity

  The course is formed from 12 lessons and Final exam. Lessons contains theory and practical exercises. Lessons are conducted in order.

  Location and Time

  Course environment is Metropolia's Moodle and course can be done in own pace.

•     Basic Excel 365 TT00EW23-3004 01.05.2022-31.08.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  The course will get acquainted with the use of Excel spreadsheet software. The goal is to give a full picture of the foundations of the spreadsheet and use of the Excel program.
  
  The course goes through e.g. worksheet processing, creating formulas, linking tables, creation of diagrams and design of the sheet.
  
  The course has been prepared for Excel 365 and Excel 2019 versions. Instructions are also suitable for browser-based Excel and for earlier versions of Excel.
  
  The course is also suitable for contra-starters.

  Course contents

  The course is formed from 12 lessons, which contains theory and practical exercises.
  
  Before lessons will be presented spreadsheet activity using a simple example.

  Further information

  Practical examples and exercises are done at the student's own workstation.
  
  Free Month Trial of Office 365, containing Excel 365 software can be downloaded from Microsoft.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in study environment.

  Planned learning activities and teaching methods

  Course is 100% online (self-study) course which can be done in own pace.
  
  The course is formed from 12 lessons and Final exam (online). Lessons contains theory and practical exercises. Lessons are conducted in order.
  
  Note that the lessons can include several pages. The link to the next page is at the end of the previous page. There's an end-of-lesson link on the last page.

  Assessment methods and criteria

  The course receives an accepted entry after all the 12 lessons of the course and Final Test has been done approved.
  
  The final exam has ? 50 multiple choice tasks and has a duration of 150 minutes.
  
  The lowest approval score is 700/1000. If the result falls below it, the test must be renewed. Final exam can be renewed 3 times!

  Language of instruction

  Tuition in Finnish

  Timing

  01.05.2022 - 31.08.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLMETS
  
  Metropolia's Degree Students
  Go to Moodle -> https://moodle.metropolia.fi/course/view.php?id=4075
  Enrolment key: Eskeli

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Content periodicity

  The course is formed from 12 lessons and Final exam. Lessons contains theory and practical exercises. Lessons are conducted in order.

  Location and Time

  Course environment is Metropolia's Moodle and course can be done in own pace.

•     Basic Network Analyzing with Wireshark TT00DC88-3007 01.01.2022-31.12.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  Course is designed to confirm individual competencies in using Wireshark to locate the cause of network problems (poor performance or security-
  related) and confirm your knowledge of TCP /IP network communications in general. Course prepares for WCNA Certification.

  Course contents

  Wiresharkin toiminnallisuus
  TCP/IP-verkkokommunikointi
  Verkon vianetsintä
  Verkkoturvallisuus

  Assessment criteria

  Satisfactory

  Student knows basics of network analyzing and is able to use Wireshark to analyze and detect network problems with assistance;

  Good

  Student knows very well network analyzing principles, and is able to use Wireshark to detect, analyze and problem-solve network problems;

  Excellent

  Student has excellent abilities to analyze network problems, and detect faults and do efficient troubleshooting, and able to take WCNA-certification's exam.

  ---

  Mode of delivery

  Distance learning

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course.
  
  The final test contains 60 multi-choice questions and its duration is 150 minutes.

  Assessment methods and criteria

  Practice Labs
  Final test
  
  The final test contains 60 multi-choice questions and its duration is 150 minutes.
  
  The minimum passing score for the test is 700. If not achieved, the student needs to take another test. The retake limit is 3!

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  Metropolia's Degree Students shall enroll to this course with instructions below.
  
  - Work space: https://moodle.metropolia.fi/course/view.php?id=3700
  - Key: ethereal
  - Exam key 1: Puteritsi

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Final exam retake limit is 3!

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Study place and Timetable is totally up to student her-/himself.

•     Basics of Information Security TT00EL92-3003 01.08.2021-31.12.2021  6 credits  (ATX21TV) + -
  Learning outcomes of the course

  After the course, the student has basic knowledge of information security and what is the meaning of information security for the companies. He or she knows the basic concepts and how basic security mechanisms work. He or she knows different cryptographic methods from the past to now.

  Prerequisites and co-requisites

  Introduction to Computing,
  Setting Up and Usage of Personal Computer (PC)

  Course contents

  - basic concepts of information security
  - company's Information Security Policy & Information Security Plan
  - different vulnerabilities, how to find them and how to protect
  - application security
  - safe use of computers
  - server security (backups, fault tolerance)
  - authentication
  - network security
  - basics of cryptography, historical view, modern crpyptographic methods, symmetric & asymmetric methods, passwords, digital signatures

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course.
  
  The theory is studied by own pace using course Moodle lessons and course literature.
  
  At the end of the course final tests are taken (on-line Moodle tests)

  Assessment methods and criteria

  The final test covers all subjects of the course. The test contains ?80 multi-choice questions and the duration is 150 minutes.
  
  The minimum passing score for the test is 700/1000. If not achieved, the student needs to retake the test.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 6 credits

  Group(s)

  • ATX21TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student
  - Go to https://moodle.metropolia.fi/course/view.php?id=1207
  - Enrolment key: turva
  - Follow instructions
  If you have problems with this course, please contact to Janne Salonen.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Basics of Information Security TT00ER70-3003 01.01.2022-31.12.2022  6 credits  (ATX22TV) + -
  Learning outcomes of the course

  This course is designed for network and security administrators and those with similar job functions which have two years of experience with general networking and basic security knowledge. After the course, the student has basic knowledge of information security and what is the meaning of information security for the companies. He or she knows the basic concepts and how basic security mechanisms work. He or she knows different cryptographic methods from the past to now.

  Course contents

  The course consists of three topics: information security, cryptology and applications security. The course gives assurance that you can handle setting up secure environments and handle the challenging situations surrounding security breaches, including the following skills:
  
  Security fundamentals
  Basic risk identification and analysis
  Threat identification and assessment
  How to secure IT infrastructure security
  Cryptography
  Operational security and general security processes
  Incident response and business continuity

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  The course lessons are based on Metropolia lecture handouts, CEH9, Cisco Learning, Microsoft Learning, and other Internet documents.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course. The theory is studied by own pace using course Moodle lessons and course literature.
  
  At the end of the course final tests are taken (on-line Moodle tests).

  Assessment methods and criteria

  The minimum passing score for the Final test is 700/1000. If not achieved, the student needs to retake the test.
  
  Final test will be taken remotely and the course is graded Pass/Fail.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 6 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLMENT
  
  Metropolia's Degree Students
  
  Go to: https://moodle.metropolia.fi/course/view.php?id=2863
  Enrolment key: turva

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered in Metropolia's Moodle environment and you can do this course in your own pace.

•     Basics of Information Security TT00EL92-3005 01.01.2022-31.12.2022  6 credits  (ATX22TV) + -
  Learning outcomes of the course

  After the course, the student has basic knowledge of information security and what is the meaning of information security for the companies. He or she knows the basic concepts and how basic security mechanisms work. He or she knows different cryptographic methods from the past to now.

  Prerequisites and co-requisites

  Introduction to Computing,
  Setting Up and Usage of Personal Computer (PC)

  Course contents

  - basic concepts of information security
  - company's Information Security Policy & Information Security Plan
  - different vulnerabilities, how to find them and how to protect
  - application security
  - safe use of computers
  - server security (backups, fault tolerance)
  - authentication
  - network security
  - basics of cryptography, historical view, modern crpyptographic methods, symmetric & asymmetric methods, passwords, digital signatures

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course.
  
  The theory is studied by own pace using course Moodle lessons and course literature.
  
  At the end of the course final tests are taken (on-line Moodle tests)

  Assessment methods and criteria

  The final test covers all subjects of the course. The test contains ?80 multi-choice questions and the duration is 150 minutes.
  
  The minimum passing score for the test is 700/1000. If not achieved, the student needs to retake the test.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 6 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student
  - Go to https://moodle.metropolia.fi/course/view.php?id=1207
  - Enrolment key: turva
  - Follow instructions
  If you have problems with this course, please contact to Janne Salonen.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Basics of Information Security TT00EL92-3006 01.01.2022-31.12.2022  6 credits  (ATX22TV) + -
  Learning outcomes of the course

  After the course, the student has basic knowledge of information security and what is the meaning of information security for the companies. He or she knows the basic concepts and how basic security mechanisms work. He or she knows different cryptographic methods from the past to now.

  Prerequisites and co-requisites

  Introduction to Computing,
  Setting Up and Usage of Personal Computer (PC)

  Course contents

  - basic concepts of information security
  - company's Information Security Policy & Information Security Plan
  - different vulnerabilities, how to find them and how to protect
  - application security
  - safe use of computers
  - server security (backups, fault tolerance)
  - authentication
  - network security
  - basics of cryptography, historical view, modern crpyptographic methods, symmetric & asymmetric methods, passwords, digital signatures

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course.
  
  The theory is studied by own pace using course Moodle lessons and course literature.
  
  At the end of the course final tests are taken (on-line Moodle tests)

  Assessment methods and criteria

  The final test covers all subjects of the course. The test contains ?80 multi-choice questions and the duration is 150 minutes.
  
  The minimum passing score for the test is 700/1000. If not achieved, the student needs to retake the test.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 6 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student
  - Go to https://moodle.metropolia.fi/course/view.php?id=1207
  - Enrolment key: turva
  - Follow instructions
  If you have problems with this course, please contact to Janne Salonen.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Basics of Information Security TT00ER70-3004 01.08.2021-31.07.2022  6 credits  (DiplomaCS) + -
  Learning outcomes of the course

  This course is designed for network and security administrators and those with similar job functions which have two years of experience with general networking and basic security knowledge. After the course, the student has basic knowledge of information security and what is the meaning of information security for the companies. He or she knows the basic concepts and how basic security mechanisms work. He or she knows different cryptographic methods from the past to now.

  Course contents

  The course consists of three topics: information security, cryptology and applications security. The course gives assurance that you can handle setting up secure environments and handle the challenging situations surrounding security breaches, including the following skills:
  
  Security fundamentals
  Basic risk identification and analysis
  Threat identification and assessment
  How to secure IT infrastructure security
  Cryptography
  Operational security and general security processes
  Incident response and business continuity

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in Metropolia's Moodle environment.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.07.2022

  • 6 credits

  Group(s)

  • DiplomaCS

  Seats

  0 - 100

  Teacher(s)

  Virve Prami

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Depends on the student's baseline

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is 100% online (Self-Study) course and it can be done in own pace. Course environment is Metropolia's Moodle.

•     Basics of Information Security TT00EL92-3007 15.09.2021-31.12.2025  6 credits  (Polkuopinnot_NonStop) + -
  Learning outcomes of the course

  After the course, the student has basic knowledge of information security and what is the meaning of information security for the companies. He or she knows the basic concepts and how basic security mechanisms work. He or she knows different cryptographic methods from the past to now.

  Prerequisites and co-requisites

  Introduction to Computing,
  Setting Up and Usage of Personal Computer (PC)

  Course contents

  - basic concepts of information security
  - company's Information Security Policy & Information Security Plan
  - different vulnerabilities, how to find them and how to protect
  - application security
  - safe use of computers
  - server security (backups, fault tolerance)
  - authentication
  - network security
  - basics of cryptography, historical view, modern crpyptographic methods, symmetric & asymmetric methods, passwords, digital signatures

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course.
  
  The theory is studied by own pace using course Moodle lessons and course literature.
  
  At the end of the course final tests are taken (on-line Moodle tests)

  Assessment methods and criteria

  The final test covers all subjects of the course. The test contains ?80 multi-choice questions and the duration is 150 minutes.
  
  The minimum passing score for the test is 700/1000. If not achieved, the student needs to retake the test.

  Language of instruction

  Tuition in Finnish

  Timing

  15.09.2021 - 31.12.2025

  • 6 credits

  Group(s)

  • Polkuopinnot_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student
  - Go to https://moodle.metropolia.fi/course/view.php?id=1207
  - Enrolment key: turva
  - Follow instructions
  If you have problems with this course, please contact to Janne Salonen.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Basics of Virtualization and Cloud Computing TX00DH60-3004 23.08.2021-17.10.2021  5 credits  (TXK21S2) + -
  Learning outcomes of the course

  After completing the course studetn know different virtualization technologies and applications. The student can design, implement and test simple open source based virtual server system and choose the suitable virtualization technologies for the services.

  Prerequisites and co-requisites

  Student can install and administer Linux-servers and IP-networks.

  Course contents

  Benefits and challenges of virtualization
  Implementation of virtualization: full scale virtualization, paravirtualization and containers
  Benefits of virtualization in SMBs
  Seminar presentations about virtualization

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TXK21S2

  Seats

  0 - 30

  Teacher(s)

  Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Biomechanics and Motion Measurement TX00CG24-3009 23.08.2021-17.10.2021  5 credits  (TVT20-H) + -
  Learning outcomes of the course

  After completing the course, the student understands the key role of physics in describing the behavior of the human body, and is able to model forces incident on bones and muscles in various situations involving strain and motion, becomes acquainted with equipment specialized to measuring and analyzing different parameters relevant to human motion, and applies learned knowledge.

  Course contents

  ? Statics and equilibrium
  ? Rigid body dynamics
  ? Equipment for motion measurement
  ? Principles of motion analysis
  ? Senses and motion

  Assessment criteria

  Satisfactory

  Student recognizes the most essential concepts introduced during the course, and is able to handle simple computational and experimental problems.

  Good

  Student understands the relevant physical principles introduced during the course, and is able to solve problems requiring advanced computational skills, is capable of performing both the measurements and their subsequent analysis in a careful and accurate manner.

  Excellent

  Student understands the relevant physical principles introduced during the course, and is able to solve problems requiring advanced computational skills, is capable of performing both the measurements and their subsequent analysis in a careful and accurate manner, recognizes connections between various subjects, is able to utilize this understanding to solving advanced problems, and shows initiative in performing measurements, analyzing them, and handling challenging situations.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  01.01.2020 - 01.01.2020

  • 5 credits

  Group(s)

  • TVT20-H

  Seats

  0 - 40

  Teacher(s)

  Anu Valtonen, Juha Kopu

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Blockchain and Cryptocurrency fundamentals TT00DU86-3004 01.01.2022-31.12.2022  5 credits  (ATX22TV) + -
  Learning outcomes of the course

  A comprehensive course to learn about Blockchain and Cryptocurrency. The students first will get introduced about the idea behind blockchain architecture, and how such a concept can be beneficial and practical, the challenges along the way, and how to tackle them. Then they will get familiar with cryptocurrency, an example of one of the applications of blockchain, and how they can purchase and store them.
  This course is 100% virtual thanks to the comprehensive content made for this course.
  The student will pass this course after submitting required assignments, quizzes, projects, and essays.

  Course contents

  Software Architecture of the Blockchain - Peer-to-Peer Systems (P2P) - The importance and use cases - Ownership - Hashing - Cryptography - Transactions - Blocks - Mining, Verifying and Rewards - Limitations

  Assessment criteria

  Satisfactory

  Evaluation criteria - satisfactory (1-2)
  - The students understand the concept of blockchain.
  - The student has a general understanding over the advantageous of blockchain and can briefly explain them.
  - The students understand the application of cryptocurrency.

  Good

  - The student is familiar with the limitations of blockchain systems.
  - The student understands blocks, transactions and how they work and keep blockchain alive.

  Excellent

  - The student can fully demonstrate the processes of mining and reward systems in blockchain.
  - The students know how to purchase and store cryptocurrencies.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online

  Planned learning activities and teaching methods

  - Tutorial Videos
  - Assignments
  - Quizzes
  - Project
  - Essay
  - Self-study

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     C - Programming TT00VI06-3012 01.08.2021-31.12.2021  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  Understanding procedural programming.
  
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  
  Data streams and files
  - The student understands the purpose of files and data streams.
  
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  
  Data streams and files:
  - The student is able to write programs, which read and write files.
  
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  
  Data streams and files:
  - The student is able to write programs which update files.
  
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C - Programming TT00CB05-3010 01.08.2021-31.12.2021  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  Understanding procedural programming.
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  Data streams and files
  - The student understands the purpose of files and data streams.
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  Data streams and files:
  - The student is able to write programs, which read and write files.
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  Data streams and files:
  - The student is able to write programs which update files.
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to student her-/himself.

•     C - Programming TT00CB05-3015 03.11.2021-27.02.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  Understanding procedural programming.
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  Data streams and files
  - The student understands the purpose of files and data streams.
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  Data streams and files:
  - The student is able to write programs, which read and write files.
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  Data streams and files:
  - The student is able to write programs which update files.
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  03.11.2021 - 27.02.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to student her-/himself.

•     C - Programming TT00VI06-3015 03.11.2021-27.02.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  Understanding procedural programming.
  
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  
  Data streams and files
  - The student understands the purpose of files and data streams.
  
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  
  Data streams and files:
  - The student is able to write programs, which read and write files.
  
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  
  Data streams and files:
  - The student is able to write programs which update files.
  
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  03.11.2021 - 27.02.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C - Programming TT00VI06-3016 28.02.2022-06.08.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  Understanding procedural programming.
  
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  
  Data streams and files
  - The student understands the purpose of files and data streams.
  
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  
  Data streams and files:
  - The student is able to write programs, which read and write files.
  
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  
  Data streams and files:
  - The student is able to write programs which update files.
  
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  28.02.2022 - 06.08.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C - Programming TT00CB05-3016 28.02.2022-06.08.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  Understanding procedural programming.
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  Data streams and files
  - The student understands the purpose of files and data streams.
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  Data streams and files:
  - The student is able to write programs, which read and write files.
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  Data streams and files:
  - The student is able to write programs which update files.
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  28.02.2022 - 06.08.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to student her-/himself.

•     C - Programming TT00VI06-3019 01.01.2022-31.12.2022  3 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  Understanding procedural programming.
  
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  
  Data streams and files
  - The student understands the purpose of files and data streams.
  
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  
  Data streams and files:
  - The student is able to write programs, which read and write files.
  
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  
  Data streams and files:
  - The student is able to write programs which update files.
  
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C - Programming TT00CB05-3019 01.01.2022-31.12.2022  3 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  Understanding procedural programming.
  Ability to implement interactive programs using different control structures. Ability to divide the program into sub programs and to use parameters. Ability to use array data structure.

  Course contents

  Elements of a program (C): variables, constants, types, expressions, arrays, control structures, input and output, sub programs and parameters.

  Assessment criteria

  Satisfactory

  Pointers and data structures (arrays, structs, linked lists)
  - The student is able to reference basic data structures using pointers (especially parameters).
  - The student understands what linked data structures are.
  Data streams and files
  - The student understands the purpose of files and data streams.
  Dynamic memory allocation
  - The student understands the differences between static, automatic and dynamic memory allocation.
  C standard library
  - The student is able to interpret the function declarations in standard library documentation.

  Good

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to declare a self referential pointer.
  - The student is able to describe the operations and parameters of linked structures.
  Data streams and files:
  - The student is able to write programs, which read and write files.
  Dynamic memory allocation:
  - The student knows how to allocate and free memory dynamically.
  C standard library:
  - The student is able to use C standard library.

  Excellent

  Pointers and data structures (arrays, structs, linked lists):
  - The student is able to understand the stucture, control flow and purpose of any program, which is written using pointers.
  - The student is able to describe the operations of a queue and a stack.
  Data streams and files:
  - The student is able to write programs which update files.
  Dynamic memory allocation:
  - The student is able to implement a queue and a stack using dynamic memory allocation.
  C standard library:
  - The student is able to explain and teach other people how to use C standard library.

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to student her-/himself.

•     C Programming in IoT Devices TX00DR64-3003 23.08.2021-17.10.2021  5 credits  (ICT20-SI1) + -
  Learning outcomes of the course

  On completion of the course the student understands principles of procedural programming. He or she is familiar with the ANSI C programming language and knows the control structures, data types and important standard functions. Additionally the student understands the fundamentals of software development in embedded environment and he or she is able to design and debug a program for embedded platform.

  Prerequisites and co-requisites

  Smart IoT-devices course or equivalent knowledge in digital systems, hardware and programming fundamentals.

  Course contents

  - C language fundamentals
  - Application development using C
  - Principles and process of software development
  - Modular organization of programs
  - Structured algorithms and structured data
  - Development environments in programming
  - Debugging
  - Software development and testing in embedded systems

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT20-SI1

  Seats

  0 - 40

  Teacher(s)

  Keijo Länsikunnas

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     C Programming in IoT Devices TX00DR64-3004 23.08.2021-17.10.2021  5 credits  (ICT20-SI2) + -
  Learning outcomes of the course

  On completion of the course the student understands principles of procedural programming. He or she is familiar with the ANSI C programming language and knows the control structures, data types and important standard functions. Additionally the student understands the fundamentals of software development in embedded environment and he or she is able to design and debug a program for embedded platform.

  Prerequisites and co-requisites

  Smart IoT-devices course or equivalent knowledge in digital systems, hardware and programming fundamentals.

  Course contents

  - C language fundamentals
  - Application development using C
  - Principles and process of software development
  - Modular organization of programs
  - Structured algorithms and structured data
  - Development environments in programming
  - Debugging
  - Software development and testing in embedded systems

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT20-SI2

  Seats

  0 - 40

  Teacher(s)

  Keijo Länsikunnas

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     C# Programming Fundamentals TT00AC49-3013 01.08.2021-31.12.2021  4 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing the course the student understands the basics of the .NET-architecture. She/he will also be able to understand, write and debug simple C# programs.

  Course contents

  Introduction to C#, basic structure of a program, datatypes, operators, conditioal statements, exceptions, loops, arrays, basics of object-oriented programming, polymorfism in object-oriented programming, string handling, file handling

  Assessment criteria

  Satisfactory

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a simple program structure;
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;

  Good

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions.
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions.

  Excellent

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions and critical evaluation.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions and critical evaluation.
  
  Subroutines:
  - the student understands what subroutine is and is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions and critical evaluation.

  Further information

  K (not translated)

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 4 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  4 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C# Programming Fundamentals TT00AC49-3016 03.11.2021-27.02.2022  4 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course the student understands the basics of the .NET-architecture. She/he will also be able to understand, write and debug simple C# programs.

  Course contents

  Introduction to C#, basic structure of a program, datatypes, operators, conditioal statements, exceptions, loops, arrays, basics of object-oriented programming, polymorfism in object-oriented programming, string handling, file handling

  Assessment criteria

  Satisfactory

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a simple program structure;
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;

  Good

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions.
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions.

  Excellent

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions and critical evaluation.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions and critical evaluation.
  
  Subroutines:
  - the student understands what subroutine is and is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions and critical evaluation.

  Further information

  K (not translated)

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  03.11.2021 - 27.02.2022

  • 4 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  4 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C# Programming Fundamentals TT00AC49-3017 28.02.2022-06.08.2022  4 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course the student understands the basics of the .NET-architecture. She/he will also be able to understand, write and debug simple C# programs.

  Course contents

  Introduction to C#, basic structure of a program, datatypes, operators, conditioal statements, exceptions, loops, arrays, basics of object-oriented programming, polymorfism in object-oriented programming, string handling, file handling

  Assessment criteria

  Satisfactory

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a simple program structure;
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;

  Good

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions.
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions.

  Excellent

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions and critical evaluation.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions and critical evaluation.
  
  Subroutines:
  - the student understands what subroutine is and is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions and critical evaluation.

  Further information

  K (not translated)

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  28.02.2022 - 06.08.2022

  • 4 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  4 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C# Programming Fundamentals TT00AC49-3020 01.01.2022-31.12.2022  4 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  After completing the course the student understands the basics of the .NET-architecture. She/he will also be able to understand, write and debug simple C# programs.

  Course contents

  Introduction to C#, basic structure of a program, datatypes, operators, conditioal statements, exceptions, loops, arrays, basics of object-oriented programming, polymorfism in object-oriented programming, string handling, file handling

  Assessment criteria

  Satisfactory

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a simple program structure;
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;

  Good

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions.
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions.

  Excellent

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions and critical evaluation.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions and critical evaluation.
  
  Subroutines:
  - the student understands what subroutine is and is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions and critical evaluation.

  Further information

  K (not translated)

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 4 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  4 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C# Programming Fundamentals TT00AC49-3021 15.09.2021-31.12.2025  4 credits  (Polkuopinnot_NonStop, ...) + -
  Learning outcomes of the course

  After completing the course the student understands the basics of the .NET-architecture. She/he will also be able to understand, write and debug simple C# programs.

  Course contents

  Introduction to C#, basic structure of a program, datatypes, operators, conditioal statements, exceptions, loops, arrays, basics of object-oriented programming, polymorfism in object-oriented programming, string handling, file handling

  Assessment criteria

  Satisfactory

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a simple program structure;
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;

  Good

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions.
  
  Subroutines:
  - the student understands what subroutine is, is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions.

  Excellent

  Algorithms and control structures:
  - the student understands what the different control structures are and knows what kind of a structure can be used in different situations;
  - the student can explain a relatively complex program structure;
  - the student shows independent solutions and critical evaluation.
  
  Variables, constants and data types:
  - the student understands what variables, constants and data types are;
  - the student shows independent solutions and critical evaluation.
  
  Subroutines:
  - the student understands what subroutine is and is able to name it and call it from the main program;
  - the student is able to write relatively complex subroutines with elegant solutions;
  - the student shows independent solutions and critical evaluation.

  Further information

  K (not translated)

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  15.09.2021 - 31.12.2025

  • 4 credits

  Group(s)

  • Polkuopinnot_NonStop
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  4 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     C++ Programming TT00CB04-3010 01.08.2021-31.12.2021  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  The student is familiar with C++ language and its specific features in object-oriented programming. The student knows how to define a class, instantiate it and write code, in which the objets created are used. The student knows how to make objects interact with each other, how to use inheritance and how to use dynamic binding.
  The student knows how to define and use generic functions and classes as well as operator functions

  Course contents

  - automatic and dynamic creation of an object,
  - constructors and destructors,
  - inheritance, associations, aggregation,
  - function overloading,
  - virtual functions and dynamic binding,
  - various parameter types,
  - copy constructor,
  - operator overloading,
  - generic classes and functions,
  - standard class library.

  Assessment criteria

  Satisfactory

  After completing this course the student will
  - understand the difference between a class and an object and knows how to use straightforward pre-coded classes in a software application
  - understands why classes are generally speaking necessary and how they are used (the importance of differentiating between implementation and user interface)
  - is able to design and use simple classes
  - understands the goal of making classes to be applicable for multiple purposes
  - understands how the vector class model operates and knows how to correctly use it instead of a C language array

  Good

  After completing this course the student will
  - understand the benefits and disadvantages of dynamic memory management when designing and using objects
  - when designing classes understand and be prepared for the challenges brought by any dynamic data members (need for a destructor, need for a copy constructor, need for an assignment operator etc.)
  - knows how to select a suitable class relation type (inheritance, association, aggregation) according to the situation when using an existing class to implement a new class
  - also knows how to implement a new class using the class relation types mentioned above
  - understands the implementation differences between various STL container class models thus being able to select a suitable model based on the requirements of the current application

  Excellent

  After completing this course the student will
  - deeply understand the meaning of function models and class models and how these operate on the compiler level
  - knows when designing classes how to be prepared for eventual memory leaks and knows how to prevent these leaks in all situations (exceptional situations included)
  - is able to very expertly use pointers, not just by trial and error (defining a pointer, indirect referencing, using references)

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in Study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     C++ Programming TT00CB04-3014 03.11.2021-27.02.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  The student is familiar with C++ language and its specific features in object-oriented programming. The student knows how to define a class, instantiate it and write code, in which the objets created are used. The student knows how to make objects interact with each other, how to use inheritance and how to use dynamic binding.
  The student knows how to define and use generic functions and classes as well as operator functions

  Course contents

  - automatic and dynamic creation of an object,
  - constructors and destructors,
  - inheritance, associations, aggregation,
  - function overloading,
  - virtual functions and dynamic binding,
  - various parameter types,
  - copy constructor,
  - operator overloading,
  - generic classes and functions,
  - standard class library.

  Assessment criteria

  Satisfactory

  After completing this course the student will
  - understand the difference between a class and an object and knows how to use straightforward pre-coded classes in a software application
  - understands why classes are generally speaking necessary and how they are used (the importance of differentiating between implementation and user interface)
  - is able to design and use simple classes
  - understands the goal of making classes to be applicable for multiple purposes
  - understands how the vector class model operates and knows how to correctly use it instead of a C language array

  Good

  After completing this course the student will
  - understand the benefits and disadvantages of dynamic memory management when designing and using objects
  - when designing classes understand and be prepared for the challenges brought by any dynamic data members (need for a destructor, need for a copy constructor, need for an assignment operator etc.)
  - knows how to select a suitable class relation type (inheritance, association, aggregation) according to the situation when using an existing class to implement a new class
  - also knows how to implement a new class using the class relation types mentioned above
  - understands the implementation differences between various STL container class models thus being able to select a suitable model based on the requirements of the current application

  Excellent

  After completing this course the student will
  - deeply understand the meaning of function models and class models and how these operate on the compiler level
  - knows when designing classes how to be prepared for eventual memory leaks and knows how to prevent these leaks in all situations (exceptional situations included)
  - is able to very expertly use pointers, not just by trial and error (defining a pointer, indirect referencing, using references)

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in Study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  03.11.2021 - 27.02.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     C++ Programming TT00CB04-3015 28.02.2022-06.08.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  The student is familiar with C++ language and its specific features in object-oriented programming. The student knows how to define a class, instantiate it and write code, in which the objets created are used. The student knows how to make objects interact with each other, how to use inheritance and how to use dynamic binding.
  The student knows how to define and use generic functions and classes as well as operator functions

  Course contents

  - automatic and dynamic creation of an object,
  - constructors and destructors,
  - inheritance, associations, aggregation,
  - function overloading,
  - virtual functions and dynamic binding,
  - various parameter types,
  - copy constructor,
  - operator overloading,
  - generic classes and functions,
  - standard class library.

  Assessment criteria

  Satisfactory

  After completing this course the student will
  - understand the difference between a class and an object and knows how to use straightforward pre-coded classes in a software application
  - understands why classes are generally speaking necessary and how they are used (the importance of differentiating between implementation and user interface)
  - is able to design and use simple classes
  - understands the goal of making classes to be applicable for multiple purposes
  - understands how the vector class model operates and knows how to correctly use it instead of a C language array

  Good

  After completing this course the student will
  - understand the benefits and disadvantages of dynamic memory management when designing and using objects
  - when designing classes understand and be prepared for the challenges brought by any dynamic data members (need for a destructor, need for a copy constructor, need for an assignment operator etc.)
  - knows how to select a suitable class relation type (inheritance, association, aggregation) according to the situation when using an existing class to implement a new class
  - also knows how to implement a new class using the class relation types mentioned above
  - understands the implementation differences between various STL container class models thus being able to select a suitable model based on the requirements of the current application

  Excellent

  After completing this course the student will
  - deeply understand the meaning of function models and class models and how these operate on the compiler level
  - knows when designing classes how to be prepared for eventual memory leaks and knows how to prevent these leaks in all situations (exceptional situations included)
  - is able to very expertly use pointers, not just by trial and error (defining a pointer, indirect referencing, using references)

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in Study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  28.02.2022 - 06.08.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     C++ Programming TT00CB04-3018 01.01.2022-31.12.2022  3 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  The student is familiar with C++ language and its specific features in object-oriented programming. The student knows how to define a class, instantiate it and write code, in which the objets created are used. The student knows how to make objects interact with each other, how to use inheritance and how to use dynamic binding.
  The student knows how to define and use generic functions and classes as well as operator functions

  Course contents

  - automatic and dynamic creation of an object,
  - constructors and destructors,
  - inheritance, associations, aggregation,
  - function overloading,
  - virtual functions and dynamic binding,
  - various parameter types,
  - copy constructor,
  - operator overloading,
  - generic classes and functions,
  - standard class library.

  Assessment criteria

  Satisfactory

  After completing this course the student will
  - understand the difference between a class and an object and knows how to use straightforward pre-coded classes in a software application
  - understands why classes are generally speaking necessary and how they are used (the importance of differentiating between implementation and user interface)
  - is able to design and use simple classes
  - understands the goal of making classes to be applicable for multiple purposes
  - understands how the vector class model operates and knows how to correctly use it instead of a C language array

  Good

  After completing this course the student will
  - understand the benefits and disadvantages of dynamic memory management when designing and using objects
  - when designing classes understand and be prepared for the challenges brought by any dynamic data members (need for a destructor, need for a copy constructor, need for an assignment operator etc.)
  - knows how to select a suitable class relation type (inheritance, association, aggregation) according to the situation when using an existing class to implement a new class
  - also knows how to implement a new class using the class relation types mentioned above
  - understands the implementation differences between various STL container class models thus being able to select a suitable model based on the requirements of the current application

  Excellent

  After completing this course the student will
  - deeply understand the meaning of function models and class models and how these operate on the compiler level
  - knows when designing classes how to be prepared for eventual memory leaks and knows how to prevent these leaks in all situations (exceptional situations included)
  - is able to very expertly use pointers, not just by trial and error (defining a pointer, indirect referencing, using references)

  Further information

  Online course

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in Study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop)
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     C/C++ Programming TX00CR60-3009 23.08.2021-17.10.2021  5 credits  (TVT19K-O) + -
  Learning outcomes of the course

  Student will learn C and C++ programming languages.

  Prerequisites and co-requisites

  Ohjelmoinnin perusosaaminen. (not translated)

  Course contents

  Procedural programming based on the C-language. The focus will be on pointers and the memory management. Object oriented programming using the C++ language.

  Further information

  Tieto- ja viestintätekniikan tutkinto-ohjelman valinnainen opintojakso. (not translated)

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  24.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT19K-O

  Seats

  0 - 36

  Teacher(s)

  Juha Kämäri

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     CISSP: Certified Information System Security Professional TT00CR29-3008 01.08.2021-31.12.2021  8 credits  (ATX21TV) + -
  Learning outcomes of the course

  This course is an review course that contains information security concepts and industry best practices, covering the 8 domains of the CISSP Common Body of Knowledge (CBK)®:
  • Security and Risk Management
  • Asset Security
  • Security Engineering
  • Communications and Network Security
  • Identity and Access Management
  • Security Assessment and Testing
  • Security Operations
  • Software Development Security
  
  This course will expand upon your knowledge by addressing the essential elements of those eight domains that comprise a Common Body of Knowledge (CBK)® for information systems security professionals. The course offers a job-related approach to the security process and will prepare you to pass the 2015 version of the CISSP® exam.

  Course contents

  In this course, you will identify and reinforce the major security subjects from the eight domains of the (ISC)2 CISSP CBK.
  
  
  Course Content
  
  Module 1: Security and Risk Management
  Module 1.1: Security Governance Principles
  Module 1.2: Compliance
  Module 1.3: Professional Ethics
  Module 1.4: Security Documentation
  Module 1.5: Risk Management
  Module 1.6: Threat Modeling
  Module 1.7: Business Continuity Plan Fundamentals
  Module 1.8: Acquisition Strategy and Practice
  Module 1.9: Personnel Security Policies
  Module 1.10: Security Awareness and Training
  
  Module 2: Asset Security
  Module 2.1: Asset Classification
  Module 2.2: Privacy Protection
  Module 2.3: Asset Retention
  Module 2.4: Data Security Controls
  Module 2.5: Secure Data Handling
  Module 3: Security Engineering
  Module 3.1: Security in the Engineering Lifecycle
  Module 3.2: System Component Security
  Module 3.3: Security Models
  Module 3.4: Controls and Countermeasures in Enterprise Security
  Module 3.5: Information System Security Capabilities
  Module 3.6: Design and Architecture Vulnerability Mitigation
  Module 3.7: Vulnerability Mitigation in Embedded, Mobile, and Web-Based Systems
  Module 3.8: Cryptography Concepts
  Module 3.9: Cryptography Techniques
  Module 3.10: Site and Facility Design for Physical Security
  Module 3.11: Physical Security Implementation in Sites and Facilities
  
  Module 4: Communications and Network Security
  Module 4.1: Network Protocol Security
  Module 4.2: Network Components Security
  Module 4.3: Communication Channel Security
  Module 4.4: Network Attack Mitigation
  
  Module 5: Identity and Access Management
  Module 5.1: Physical and Logical Access Control
  Module 5.2: Identification, Authentication, and Authorization
  Module 5.3: Identity as a Service
  Module 5.4: Authorization Mechanisms
  Module 5.5: Access Control Attack Mitigation
  
  Module 6: Security Assessment and Testing
  Module 6.1: System Security Control Testing
  Module 6.2: Software Security Control Testing
  Module 6.3: Security Process Data Collection
  Module 6.4: Audits
  
  Module 7: Security Operations
  Module 7.1: Security Operations Concepts
  Module 7.2: Physical Security
  Module 7.3: Personnel Security
  Module 7.4: Logging and Monitoring
  Module 7.5: Preventative Measures
  Module 7.6: Resource Provisioning and Protection
  Module 7.7: Patch and Vulnerability Management
  Module 7.8: Change Management
  Module 7.9: Incident Response
  Module 7.10: Investigations
  Module 7.11: Disaster Recovery Planning
  Module 7.12: Disaster Recovery Strategies
  Module 7.13: Disaster Recovery Implementation
  
  Module 8: Software Development Security
  Module 8.1: Security Principles in the System Lifecycle
  Module 8.2: Security Principles in the Software Development Lifecycle
  Module 8.3: Database Security in Software Development
  Module 8.4: Security Controls in the Development Environment
  Module 8.5: Software Security Effectiveness Assessment

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in study environment.

  Planned learning activities and teaching methods

  100% Online (Self-Study) course.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2021

  • 8 credits

  Group(s)

  • ATX21TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student:
  - Go to https://moodle.metropolia.fi/course/view.php?id=144
  - Enrollment key for the course: cissp
  - Password for final exam: cissp
  
  Please review the course modules 1-8 material and then do the Final exam.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  8 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  Up to Student - course is online (Self-Study) course.

•     CISSP: Certified Information System Security Professional TT00CR29-3010 01.01.2022-31.12.2022  8 credits  (ATX22TV) + -
  Learning outcomes of the course

  This course is an review course that contains information security concepts and industry best practices, covering the 8 domains of the CISSP Common Body of Knowledge (CBK)®:
  • Security and Risk Management
  • Asset Security
  • Security Engineering
  • Communications and Network Security
  • Identity and Access Management
  • Security Assessment and Testing
  • Security Operations
  • Software Development Security
  
  This course will expand upon your knowledge by addressing the essential elements of those eight domains that comprise a Common Body of Knowledge (CBK)® for information systems security professionals. The course offers a job-related approach to the security process and will prepare you to pass the 2015 version of the CISSP® exam.

  Course contents

  In this course, you will identify and reinforce the major security subjects from the eight domains of the (ISC)2 CISSP CBK.
  
  
  Course Content
  
  Module 1: Security and Risk Management
  Module 1.1: Security Governance Principles
  Module 1.2: Compliance
  Module 1.3: Professional Ethics
  Module 1.4: Security Documentation
  Module 1.5: Risk Management
  Module 1.6: Threat Modeling
  Module 1.7: Business Continuity Plan Fundamentals
  Module 1.8: Acquisition Strategy and Practice
  Module 1.9: Personnel Security Policies
  Module 1.10: Security Awareness and Training
  
  Module 2: Asset Security
  Module 2.1: Asset Classification
  Module 2.2: Privacy Protection
  Module 2.3: Asset Retention
  Module 2.4: Data Security Controls
  Module 2.5: Secure Data Handling
  Module 3: Security Engineering
  Module 3.1: Security in the Engineering Lifecycle
  Module 3.2: System Component Security
  Module 3.3: Security Models
  Module 3.4: Controls and Countermeasures in Enterprise Security
  Module 3.5: Information System Security Capabilities
  Module 3.6: Design and Architecture Vulnerability Mitigation
  Module 3.7: Vulnerability Mitigation in Embedded, Mobile, and Web-Based Systems
  Module 3.8: Cryptography Concepts
  Module 3.9: Cryptography Techniques
  Module 3.10: Site and Facility Design for Physical Security
  Module 3.11: Physical Security Implementation in Sites and Facilities
  
  Module 4: Communications and Network Security
  Module 4.1: Network Protocol Security
  Module 4.2: Network Components Security
  Module 4.3: Communication Channel Security
  Module 4.4: Network Attack Mitigation
  
  Module 5: Identity and Access Management
  Module 5.1: Physical and Logical Access Control
  Module 5.2: Identification, Authentication, and Authorization
  Module 5.3: Identity as a Service
  Module 5.4: Authorization Mechanisms
  Module 5.5: Access Control Attack Mitigation
  
  Module 6: Security Assessment and Testing
  Module 6.1: System Security Control Testing
  Module 6.2: Software Security Control Testing
  Module 6.3: Security Process Data Collection
  Module 6.4: Audits
  
  Module 7: Security Operations
  Module 7.1: Security Operations Concepts
  Module 7.2: Physical Security
  Module 7.3: Personnel Security
  Module 7.4: Logging and Monitoring
  Module 7.5: Preventative Measures
  Module 7.6: Resource Provisioning and Protection
  Module 7.7: Patch and Vulnerability Management
  Module 7.8: Change Management
  Module 7.9: Incident Response
  Module 7.10: Investigations
  Module 7.11: Disaster Recovery Planning
  Module 7.12: Disaster Recovery Strategies
  Module 7.13: Disaster Recovery Implementation
  
  Module 8: Software Development Security
  Module 8.1: Security Principles in the System Lifecycle
  Module 8.2: Security Principles in the Software Development Lifecycle
  Module 8.3: Database Security in Software Development
  Module 8.4: Security Controls in the Development Environment
  Module 8.5: Software Security Effectiveness Assessment

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in study environment.

  Planned learning activities and teaching methods

  100% Online (Self-Study) course.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 8 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student:
  - Go to https://moodle.metropolia.fi/course/view.php?id=144
  - Enrollment key for the course: cissp
  - Password for final exam: cissp
  
  Please review the course modules 1-8 material and then do the Final exam.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  8 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  Up to Student - course is online (Self-Study) course.

•     CISSP: Certified Information System Security Professional TT00CR29-3011 01.01.2022-31.12.2022  8 credits  (ATX22TV) + -
  Learning outcomes of the course

  This course is an review course that contains information security concepts and industry best practices, covering the 8 domains of the CISSP Common Body of Knowledge (CBK)®:
  • Security and Risk Management
  • Asset Security
  • Security Engineering
  • Communications and Network Security
  • Identity and Access Management
  • Security Assessment and Testing
  • Security Operations
  • Software Development Security
  
  This course will expand upon your knowledge by addressing the essential elements of those eight domains that comprise a Common Body of Knowledge (CBK)® for information systems security professionals. The course offers a job-related approach to the security process and will prepare you to pass the 2015 version of the CISSP® exam.

  Course contents

  In this course, you will identify and reinforce the major security subjects from the eight domains of the (ISC)2 CISSP CBK.
  
  
  Course Content
  
  Module 1: Security and Risk Management
  Module 1.1: Security Governance Principles
  Module 1.2: Compliance
  Module 1.3: Professional Ethics
  Module 1.4: Security Documentation
  Module 1.5: Risk Management
  Module 1.6: Threat Modeling
  Module 1.7: Business Continuity Plan Fundamentals
  Module 1.8: Acquisition Strategy and Practice
  Module 1.9: Personnel Security Policies
  Module 1.10: Security Awareness and Training
  
  Module 2: Asset Security
  Module 2.1: Asset Classification
  Module 2.2: Privacy Protection
  Module 2.3: Asset Retention
  Module 2.4: Data Security Controls
  Module 2.5: Secure Data Handling
  Module 3: Security Engineering
  Module 3.1: Security in the Engineering Lifecycle
  Module 3.2: System Component Security
  Module 3.3: Security Models
  Module 3.4: Controls and Countermeasures in Enterprise Security
  Module 3.5: Information System Security Capabilities
  Module 3.6: Design and Architecture Vulnerability Mitigation
  Module 3.7: Vulnerability Mitigation in Embedded, Mobile, and Web-Based Systems
  Module 3.8: Cryptography Concepts
  Module 3.9: Cryptography Techniques
  Module 3.10: Site and Facility Design for Physical Security
  Module 3.11: Physical Security Implementation in Sites and Facilities
  
  Module 4: Communications and Network Security
  Module 4.1: Network Protocol Security
  Module 4.2: Network Components Security
  Module 4.3: Communication Channel Security
  Module 4.4: Network Attack Mitigation
  
  Module 5: Identity and Access Management
  Module 5.1: Physical and Logical Access Control
  Module 5.2: Identification, Authentication, and Authorization
  Module 5.3: Identity as a Service
  Module 5.4: Authorization Mechanisms
  Module 5.5: Access Control Attack Mitigation
  
  Module 6: Security Assessment and Testing
  Module 6.1: System Security Control Testing
  Module 6.2: Software Security Control Testing
  Module 6.3: Security Process Data Collection
  Module 6.4: Audits
  
  Module 7: Security Operations
  Module 7.1: Security Operations Concepts
  Module 7.2: Physical Security
  Module 7.3: Personnel Security
  Module 7.4: Logging and Monitoring
  Module 7.5: Preventative Measures
  Module 7.6: Resource Provisioning and Protection
  Module 7.7: Patch and Vulnerability Management
  Module 7.8: Change Management
  Module 7.9: Incident Response
  Module 7.10: Investigations
  Module 7.11: Disaster Recovery Planning
  Module 7.12: Disaster Recovery Strategies
  Module 7.13: Disaster Recovery Implementation
  
  Module 8: Software Development Security
  Module 8.1: Security Principles in the System Lifecycle
  Module 8.2: Security Principles in the Software Development Lifecycle
  Module 8.3: Database Security in Software Development
  Module 8.4: Security Controls in the Development Environment
  Module 8.5: Software Security Effectiveness Assessment

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find in study environment.

  Planned learning activities and teaching methods

  100% Online (Self-Study) course.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 8 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student:
  - Go to https://moodle.metropolia.fi/course/view.php?id=144
  - Enrollment key for the course: cissp
  - Password for final exam: cissp
  
  Please review the course modules 1-8 material and then do the Final exam.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  8 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  Up to Student - course is online (Self-Study) course.

•     Calibration of Measurement Devices and Data Evaluation TX00DC44-3005 02.08.2021-06.08.2021  3 credits  (ICTSUMMER) + -
  Learning outcomes of the course

  After completion of this course the student will understand how to calibrate a computer aided measurement device. He will understand to separate systematic errors and random errors, correct systematic errors and describe random errors with fundamental statistical methods. He should be able to create a visualisation of rows of measurements. The student is able to calculate the average error of the mean and to calculate error propagations.

  Prerequisites and co-requisites

  1. Fundamentals of mathematics
  2. Basics of technical science and physics

  Course contents

  1. Introduction
  2. Systematic errors and random errors, separation of them
  3. Movement and correction of a linear / non linear characteristic
  4. Example for calibration of a device and determination of the random error
  5. Range and Precision and error propagation
  6. Evaluation of series of measurements

  Assessment criteria

  Satisfactory

  - Student understands the principles of calibration
  - Student has run the lab experiment with right results
  - Student has more the 50% of the points of the written exam

  Good

  - Student understands the principles of calibration and pre calibration
  - Has run the lab experiment with right results and can calculate the precision of the device.
  - Student has more the 70% of the points of the written exam

  Excellent

  in addition to the previous,
  - Student understands the principles of calibration and pre calibration
  - Has run the lab experiment with right results and can calculate the precision of the device.
  - Student has more the 70% of the points of the written exam

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  All learning material is published online in course web-page.
  • lecture as pdf or printed out

  Assessment methods and criteria

  The course assessment is based on
  - active attendance
  - active calculation of examples by the students during the lecture
  - assessment of the lab experiment
  - written examination over 60 minutes

  Language of instruction

  English

  Timing

  02.08.2021 - 06.08.2021

  Enrollment date

  03.05.2021 - 31.07.2021

  • 3 credits

  Group(s)

  • ICTSUMMER

  Seats

  0 - 24

  Teacher(s)

  Jörg Hoffmann, Werner Trentmann

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  0-5

  International connections

  Course teachers are Prof. Dr. Jörg Hoffmann & Mr. Werner Trentmann from Osnabrück University of Applied Sciences, Germany.

•     Client Pro (MD100 and MD101) TT00EN20-3003 01.08.2021-31.12.2022  6 credits  (INSINÖÖRILIITTO) + -
  Learning outcomes of the course

  This course prepares students for the TestOut Client Pro certification exam and Microsoft’s Windows 10 (MD-100) and Managing Modern Desktops (MD-101) certification exams.
  
  Completing this course effectively prepares students to earn their Microsoft 365 Certified: Modern Desktop Administrator Associate certification.

  Course contents

  The TestOut Client Pro course focuses on teaching configuration tasks performed on the client computer by a desktop administrator in a business environment.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Course material is online.

  Planned learning activities and teaching methods

  100% online Self-study course. All you need is web browser and working network connection.

  Assessment methods and criteria

  You have two choices for completion. You can do couple of exercises from each module, and or you can do the test. This test can be found from the environment.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2022

  • 6 credits

  Group(s)

  • INSINÖÖRILIITTO

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  You have two choices for completion.
  
  You can do couple of exercises from each module or you can do the test. This test can be found from the environment.

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via LabSim -environment and timetable is totally up to student. Course can be done in own pace.

•     Client Pro (MD100 and MD101) TT00EN20-3004 01.01.2022-31.07.2023  6 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  This course prepares students for the TestOut Client Pro certification exam and Microsoft’s Windows 10 (MD-100) and Managing Modern Desktops (MD-101) certification exams.
  
  Completing this course effectively prepares students to earn their Microsoft 365 Certified: Modern Desktop Administrator Associate certification.

  Course contents

  The TestOut Client Pro course focuses on teaching configuration tasks performed on the client computer by a desktop administrator in a business environment.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Course material is online.

  Planned learning activities and teaching methods

  100% online Self-study course. All you need is web browser and working network connection.

  Assessment methods and criteria

  You have two choices for completion. You can do couple of exercises from each module, and or you can do the test. This test can be found from the environment.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.07.2023

  • 6 credits

  Group(s)

  • ATX22TV
  • ATX23TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  You have two choices for completion.
  
  You can do couple of exercises from each module or you can do the test. This test can be found from the environment.

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via LabSim -environment and timetable is totally up to student. Course can be done in own pace.

•     Cloud Security TX00EW26-3001 01.10.2021-31.12.2022  2 credits + -
  Learning outcomes of the course

  After completing the course the learner knows cloud models and architectures, and how to apply the Shared Responsibilities model to building a cloud security program. Learner also knows the impact of cloud computing on governance, legal, risk and regulatory compliance. During this course learner gains knowledge how to adapt existing security principles and practices for cloud deployments,
  including the impact of cloud on all traditional security domains. Also learner will be able to practically apply the Cloud Security Alliance Security Guidance, Cloud Controls Matris and other reserach to a cloud security program.

  Course contents

  cloud architecture, infrastructure security for cloud, managing cloud security and risk, data security for cloud computing, application security and identity management for cloud computing, cloud security operations

  ---

  Name of lecturer(s)

  Erik Pätynen

  Mode of delivery

  Distance learning

  Language of instruction

  English

  Timing

  01.10.2021 - 31.12.2022

  • 2 credits

  Seats

  0 - 100

  Teacher(s)

  Erik Pätynen

  Further information for students

  Enrol via efrom: https://elomake.metropolia.fi/lomakkeet/25240/lomake.html

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  2 credits

  Evaluation scale

  Hyväksytty/Hylätty

•     Collection and Reporting of Web Analytics Using Google Tag Manager TX00EU62-3001 02.08.2021-06.08.2021  3 credits  (ICTSUMMER) + -
  Learning outcomes of the course

  This course aims to familiarize students with different methods for reporting web analytics with Google Tag Manager and some of the most important digital marketing terms. Students will learn to manage web tags for one or multiple sites within containers, how to add/modify tracking code effectively, work with version control, manage user access, use debugger tools, and custom variables. The course will also discuss the Datalayer object of Google Tag Manager, which enables further customization for effective collection and reporting of analytical data.

  Prerequisites and co-requisites

  In order to make best use of the course content, it is recommended that students have some previous knowledge in web development and ideally with Javascript.

  Course contents

  - Roles of Google Analytics and Google Tag Manager
  - Supported 3rd party service tags
  - Custom variables
  - Fire custom tags with triggers
  - Version control and use of debugger tool
  - Datalayer object
  - DOM content scraping and data reporting through DataLayer object with Javascript

  Assessment criteria

  Satisfactory

  Student has completed all the exercises and assignments and has achieved the course objectives.

  ---

  Mode of delivery

  Distance learning

  Assessment methods and criteria

  -4 daily assignments based on the lecture content (60%)
  -1 final assignment 40%
  -Approval for all assignments are required to obtain 3 ECTS
  
  Grading scale:
  -Satisfactory/Pass: 50 - 70%
  -Good: 70% - 90%
  -Excellent: 90% - 100%

  Language of instruction

  English

  Timing

  02.08.2021 - 06.08.2021

  Enrollment date

  03.05.2021 - 31.07.2021

  • 3 credits

  Group(s)

  • ICTSUMMER

  Seats

  0 - 24

  Teacher(s)

  Vaihto Opettaja Tivi

  Further information for students

  Course teacher is Hoang Pham, M.Sc., from Business College Helsinki.

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  0-5

  Location and Time

  2.8.2021 - 6.8.2021 (afternoon 13:00-17:00)

•     Communication Networks TT00EW04-3002 01.01.2022-31.12.2022  5 credits  (ATX22TV) + -
  Learning outcomes of the course

  On completion of the course the student knows the basic structures and operating principles of different communication networks. The student knows also the basic terminology related to communication networks and is able to follow the development of new communication solutions.

  Course contents

  Standardization
  Basic principles of digital communication
  Signals carried over the network
  Speech coding methods and PCM
  Circuit and packet switched networks
  Transmission media
  Line coding and modulation
  Digital modulation methods
  Maximum transmission rate of a transmission channel
  Cellular radio principles

  Assessment criteria

  Satisfactory

  The student has achieved the course objectives fairly. The student is able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum required level. His/her competences have developed in a way that he/she may increase his/her knowledge in the given field of technology and finally work in job positions related to this field of technology.

  Good

  The student has achieved the course objectives well, even though the knowledge and skills need to be enhanced on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis. The student is able to apply the knowledge of the course in study and work situations.

  Excellent

  The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis and to present concrete development measures. The student is well prepared to apply the knowledge of the course in the study and work situations.

  Further information

  Course is for Open UAS Students.

  ---

  Mode of delivery

  Distance learning

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 500

  Teacher(s)

  Antti Koivumäki

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

•     Communication Networks TT00EW04-3001 01.08.2021-31.05.2022  5 credits  (ATX21TV) + -
  Learning outcomes of the course

  On completion of the course the student knows the basic structures and operating principles of different communication networks. The student knows also the basic terminology related to communication networks and is able to follow the development of new communication solutions.

  Course contents

  Standardization
  Basic principles of digital communication
  Signals carried over the network
  Speech coding methods and PCM
  Circuit and packet switched networks
  Transmission media
  Line coding and modulation
  Digital modulation methods
  Maximum transmission rate of a transmission channel
  Cellular radio principles

  Assessment criteria

  Satisfactory

  The student has achieved the course objectives fairly. The student is able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum required level. His/her competences have developed in a way that he/she may increase his/her knowledge in the given field of technology and finally work in job positions related to this field of technology.

  Good

  The student has achieved the course objectives well, even though the knowledge and skills need to be enhanced on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis. The student is able to apply the knowledge of the course in study and work situations.

  Excellent

  The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis and to present concrete development measures. The student is well prepared to apply the knowledge of the course in the study and work situations.

  Further information

  Course is for Open UAS Students.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Using online material requires having the book
  Tarmo Anttalainen & Ville Jääskeläinen: Introduction to Communication Networks
  available. Students can use the e-book version of the textbook at no cost.

  Planned learning activities and teaching methods

  You go through the material in the textbook and online, and do problems and exercises based on the material.

  Assessment methods and criteria

  Evaluation is based on our submissions of answers to problems and exercises.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.05.2022

  Enrollment date

  01.08.2021 - 31.05.2022

  • 5 credits

  Group(s)

  • ATX21TV

  Seats

  0 - 500

  Teacher(s)

  Antti Koivumäki

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  -

  Work placement(s)

  -

  Exam schedule

  No exam.

  International connections

  -

  Students use of time and load

  You can do the course at your own pace.

  Content periodicity

  You can do the course at your own pace.

  Location and Time

  Everything happens online.

•     CyberDefence Professional TT00EU28-3002 01.01.2022-31.07.2023  8 credits  (ATX22TV) + -
  Learning outcomes of the course

  TestOut CyberDefense Pro will help you teach students how to monitor and respond to traffic both proactively and analytically, using hands-on labs that challenge with high-stake scenarios they’ll face on the job. It covers the most up-to-date tools, like Burp Suite, Wireshark, Metaspoit, Ettercap, and Nmap, to learn job skills used by Incident Responders, Threat Intelligence Analysts, and Cybersecurity Analysts in and out of Security Operations Centers (SOC).

  Course contents

  INTRODUCTION
  Introduction to TestOut CyberDefense Pro
  
  THREAT INTELLIGENCE
  Penetration Testing Process and Types
  Threat Hunting
  Organizational Security
  Security Controls
  
  RISK MITIGATION
  Risk Identification Process
  Risk Calculation
  Risk Communication and Training
  
  SOCIAL AND PHYSICAL SECURITY
  Social Engineering
  Physical Security
  Countermeasures and Prevention
  
  RECONNAISSANCE
  Reconnaissance Overview
  Reconnaissance Countermeasures
  Scanning
  
  ENUMERATION
  Enumeration Overview
  Enumeration Countermeasures
  
  VULNERABILITY MANAGEMENT
  Vulnerability Assessment
  Vulnerability Management Life Cycle
  Vulnerability Scoring Systems
  Vulnerability Analysis
  
  IDENTITY AND ACCESS MANAGEMENT SECURITY (IAM)
  Identity and Access Management Security
  Privilege Escalation
  Identity and Access Management Threats
  Certificate Management
  
  CYBERSECURITY THREATS
  Malware
  Combat Malware
  Sniffing
  Session Hijacking
  
  INFRASTRUCTURE SECURITY
  Intrusion Detection Systems
  Firewalls
  Honeypots and DNS Sinkholes
  Web Servers
  Network Access
  Web Applications
  Specialized Technology
  
  WIRELESS AND IOT SECURITY
  Wireless Security
  Bluetooth Security
  Mobile Device Security
  Cloud Security
  Internet of Things Security
  
  INFRASTRUCTURE ANALYSIS
  Hardware Analysis
  Security Information and Event Management (SIEM)
  Log Review
  Asset Management
  Supply Chain Management
  Change Management
  Virtualization Management
  
  SOFTWARE ASSURANCE
  Software Development Overview
  Automation
  
  DATA ANALYSIS
  Data Analysis and Protection
  Hashing
  Digital Forensics
  Email Analysis
  
  INCIDENT RESPONSE
  Incident Response - Preparation
  Incident Response - Detection and Containment
  Incident Response - Eradication and Recovery
  Indicators of Compromise
  
  TESTOUT CYBERDEFENSE PRO PRACTICE EXAMS
  Prepare for TestOut CyberDefense Pro Certification
  TestOut CyberDefense Pro Domain Review

  Further information

  CompTIA Cybersecurity Analyst (CySA+) is an IT workforce certification that applies behavioral analytics to networks and devices to prevent, detect and combat cybersecurity threats through continuous security monitoring.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  All of material is online.

  Planned learning activities and teaching methods

  Course is 100% online (Self-study) course.
  
  TestOut CyberDefense Pro will make life easy for students with our turnkey, plug-n-play courseware that gives you all the learning materials you need in a safe, contained environment that works great for traditional, hybrid, and online learning. You won’t need to worry about downloads, setting up and scoring labs.
  
  With an Internet connection and a Mac or PC, students can access over a hundred different up-to-date topics and over 50 up-to-date software and tools covering:
  
  Incident response
  Security operations and monitoring
  Threat and vulnerability management
  Software and systems security
  Compliance and assessments
  And much more

  Language of instruction

  English

  Timing

  01.01.2022 - 31.07.2023

  • 8 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  Coming May 18, 2021. Pre-release access available April 20, 2021.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  8 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find online.

  International connections

  N/A

  Students use of time and load

  It's up to Student her-/himself.

  Content periodicity

  It's up to Student her-/himself.

  Location and Time

  Workpace is in TestOut LabSim environment and course can be done in own pace.

•     Data Collection and Processing TX00CG26-3009 25.10.2021-19.12.2021  5 credits  (TVT20-H) + -
  Learning outcomes of the course

  After completing the course, the student knows how to build a simple measurement system and how to connect sensors to measurement system, understands sensor operation, and manages measurement data processing and storage.

  Course contents

  ? Labview programming
  ? Development of graphical measurement application
  ? Connecting sensors to system
  ? Data processing, analysis and presentation
  ? Storing data to database

  Assessment criteria

  Satisfactory

  Student is part of a team that builds a simple measurement system and connects sensors to the system, and understands basics of sensor operation, measurement data processing and storage.

  Good

  Student builds a simple measurement system and connects sensors to the system, understands sensor operation, and manages measurement data processing and storage.

  Excellent

  Student builds a simple measurement system, connects sensors to the system, and analyzes system operation, has a high-level understanding of sensor operation, and thoroughly manages measurement data processing and storage.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  01.01.2020 - 01.01.2020

  • 5 credits

  Group(s)

  • TVT20-H

  Seats

  0 - 40

  Teacher(s)

  Saana Vallius, Joseph Hotchkiss

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Data Encryption and Cryptomathematics TX00CK78-3010 25.10.2021-19.12.2021  5 credits  (TVT19-O) + -
  Learning outcomes of the course

  The student is sufficiently familiar with algebraic theories in order to understand the operation of the most usual encryption algorithms and the basis of encryption. The student understands the basic facts of computational complexity such as the difference between polynomial and superpolynomial work of computation and the idea of probabilistic algorithms.

  Prerequisites and co-requisites

  Discrete Mathematics. Programming skills.

  Course contents

  1) Algebra and number theory
  2) Basic Terms in Cryptography
  3) Algorithms and computational complexity
  4) RSA encryption and factoring problem
  5) Discrete Logarithm problem and applying it to cryptography

  Assessment criteria

  Satisfactory

  The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level.

  Good

  The student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis.

  Excellent

  The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT19-O

  Seats

  0 - 40

  Teacher(s)

  Mikko Pere

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Data Handling and Machine Learning TX00DZ36-3002 25.10.2021-19.12.2021  5 credits  (TVT19-O) + -
  Learning outcomes of the course

  After completion of the course, the student understands the possibilities in data handling, modelling and, particularly, machine learning. The course participants have acquired hands-on experience in data storage, retrieval, and manipulation as well as the methods and tools in machine learning.

  Course contents

  - Large volumes of data in ICT business: applicability, models, opportunities, and processes, legislative and ethical constraints.
  - Data acquisition and preprocessing.
  - Data management solutions.
  - Machine learning methods (classification, association analysis, clustering, prediction of numeric values) , their fields of use and applicability.
  - Machine learning software.
  - Validation and visualisation of results.
  - Machine learning in natural language processing.

  Assessment criteria

  Satisfactory

  The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level.

  Good

  The student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis.

  Excellent

  The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT19-O

  Seats

  0 - 40

  Teacher(s)

  Juha Kopu, Vesa Ollikainen

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Data Structures and Algorithms TX00DS64-3004 23.08.2021-17.10.2021  5 credits  (TVT20K-O1) + -
  Learning outcomes of the course

  Student is familiar with basic data structures and knows about some crucial, often used algorithms. Student will have practical skills for planning and analysing algorithms. Furthermore a student familiarizes oneself with the Java Collections API module, as an example of a framework including a complete set of data structures and algorithms.

  Prerequisites and co-requisites

  Object-oriented Applications and Databases

  Course contents

  - Abstract data type
  - Data structures: linear list, stack, queue, trees, priority queue, set (hashing), graphs
  - Recursion
  - Implementation of data structures and algorithms
  - Search problem, sort problem
  - Computational complexity
  - Using Java Collections API: containers and iterators

  Assessment criteria

  Satisfactory

  Understands the principle of abstraction in programming work and is able to use different data structures offered by APIs.

  Good

  The student understands the implementation principles of different data structures and is able to choose an appropriate data structure to a problem in hand. Student is able to write algorithms to manage different data structures.

  Excellent

  The student understands and is able to analyze the computational complexity of different data structures and their algorithms.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT20K-O1

  Seats

  0 - 31

  Teacher(s)

  Juha Kämäri

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Data Structures and Algorithms TX00DS64-3005 25.10.2021-19.12.2021  5 credits  (TVT20K-O2) + -
  Learning outcomes of the course

  Student is familiar with basic data structures and knows about some crucial, often used algorithms. Student will have practical skills for planning and analysing algorithms. Furthermore a student familiarizes oneself with the Java Collections API module, as an example of a framework including a complete set of data structures and algorithms.

  Prerequisites and co-requisites

  Object-oriented Applications and Databases

  Course contents

  - Abstract data type
  - Data structures: linear list, stack, queue, trees, priority queue, set (hashing), graphs
  - Recursion
  - Implementation of data structures and algorithms
  - Search problem, sort problem
  - Computational complexity
  - Using Java Collections API: containers and iterators

  Assessment criteria

  Satisfactory

  Understands the principle of abstraction in programming work and is able to use different data structures offered by APIs.

  Good

  The student understands the implementation principles of different data structures and is able to choose an appropriate data structure to a problem in hand. Student is able to write algorithms to manage different data structures.

  Excellent

  The student understands and is able to analyze the computational complexity of different data structures and their algorithms.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT20K-O2

  Seats

  0 - 30

  Teacher(s)

  Juha Kämäri

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Database Solutions TX00CR58-3009 25.10.2021-19.12.2021  5 credits  (TVT19K-O) + -
  Learning outcomes of the course

  Upon completing the course the student knows the principles and key practices in logical and physical database design. He/she is able to model the structure and dependencies of data. The student is able to design a relational database both on database-first and code-first basis. He/she can implement a database in such a way that its structure, performance and security are of high standards. The student is familiar with challenges in object-relational mapping, and he/she masters the key related technologies. The student understands the principles of database concurrency control.

  Prerequisites and co-requisites

  Basics of object-oriented programming.
  Basic SQL knowledge.

  Course contents

  Data-first and code-first database design, normalization of databases, installation and configuration of a database server, indexing, query optimization, views, triggers, user privileges, security, backup policies, object-relational mapping and its technical solutions, means of concurrency control.

  Assessment criteria

  Satisfactory

  The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level.

  Good

  The student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis.

  Excellent

  The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  24.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT19K-O

  Seats

  0 - 36

  Teacher(s)

  Vesa Ollikainen

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Databases in Game Development TX00DO54-3004 23.08.2021-17.10.2021  5 credits  (TVT20-PE) + -
  Learning outcomes of the course

  Student improves skills in database design and game development. He is able to utilise databases in game projects.

  Course contents

  • Database design
  • Game development

  Assessment criteria

  Satisfactory

  • Student is able to implement a database according to specifications
  • Student has basic skills in game development

  Good

  • Student is able design and implement a database
  • Student has basic skills in game development
  • Student is able to utilise databases in game projects

  Excellent

  • Student is able design and implement a database
  • Student has good skills in game development
  • Student is able to utilise databases in game projects

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  01.01.2020 - 01.01.2020

  • 5 credits

  Group(s)

  • TVT20-PE

  Seats

  0 - 40

  Teacher(s)

  Heini Puuska, Antti Laiho

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Description and Modelling Techniques TX00EC75-3002 23.08.2021-17.10.2021  5 credits  (TVT20K-O1) + -
  Learning outcomes of the course

  Understanding the purpose and principles of modelling and UML description language.
  The ability to use CASE tools for software design. Understanding the relationships between the program code and UML diagrams.

  Prerequisites and co-requisites

  Object-oriented Applications and Databases

  Course contents

  - overview of modelling techniques (structural and object-based)
  - description techniques: static and dynamic model, differences
  - object-based UML modelling : use case modelling, class and object diagrams, sequence diagrams and
  state diagrams

  Assessment criteria

  Satisfactory

  The student knows the basic uses and goals for modelling. He or she can categorize the most important UML diagrams according to use. He or she can explain and give an example of a behavioral and structural diagram. He or she can use a CASE tool for producing UML diagrams.

  Good

  The student can describe the uses of different diagrams in software life cycle. He or she can use case diagrams and use case descriptions in analysing requirements. He or she can use class, sequence, and state diagrams in designing software.

  Excellent

  The student can choose relevant modelling methods applicable to a project. He or she can apply modelling and UML techniques in all phases of a software project. He or she can use diagrams to descibe a system from different abstraction levels, and from diffrent angles.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT20K-O1

  Seats

  0 - 31

  Teacher(s)

  Vesa Ollikainen

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Description and Modelling Techniques TX00EC75-3003 23.08.2021-17.10.2021  5 credits  (TVT20K-O2) + -
  Learning outcomes of the course

  Understanding the purpose and principles of modelling and UML description language.
  The ability to use CASE tools for software design. Understanding the relationships between the program code and UML diagrams.

  Prerequisites and co-requisites

  Object-oriented Applications and Databases

  Course contents

  - overview of modelling techniques (structural and object-based)
  - description techniques: static and dynamic model, differences
  - object-based UML modelling : use case modelling, class and object diagrams, sequence diagrams and
  state diagrams

  Assessment criteria

  Satisfactory

  The student knows the basic uses and goals for modelling. He or she can categorize the most important UML diagrams according to use. He or she can explain and give an example of a behavioral and structural diagram. He or she can use a CASE tool for producing UML diagrams.

  Good

  The student can describe the uses of different diagrams in software life cycle. He or she can use case diagrams and use case descriptions in analysing requirements. He or she can use class, sequence, and state diagrams in designing software.

  Excellent

  The student can choose relevant modelling methods applicable to a project. He or she can apply modelling and UML techniques in all phases of a software project. He or she can use diagrams to descibe a system from different abstraction levels, and from diffrent angles.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT20K-O2

  Seats

  0 - 30

  Teacher(s)

  Vesa Ollikainen

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Design Patterns TX00EC76-3002 25.10.2021-19.12.2021  5 credits  (TVT20K-O1) + -
  Learning outcomes of the course

  On completion of the course, the student knows the purpose of design patterns as elements of reusable object-oriented software. The student is familiar with GOF design patterns.

  Prerequisites and co-requisites

  Object-oriented programming

  Course contents

  Purposes of patterns
  Structures and beaviours of patterns
  Applications of patterns

  Assessment criteria

  Satisfactory

  Student knows best practices and design patterns.

  Good

  Student is able to design and implement programs using best practices and design patterns.

  Excellent

  Student is able to diversely design and implement programs using best practices and design patterns.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT20K-O1

  Seats

  0 - 31

  Teacher(s)

  Simo Silander

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Design Patterns TX00EC76-3003 25.10.2021-19.12.2021  5 credits  (TVT20K-O2) + -
  Learning outcomes of the course

  On completion of the course, the student knows the purpose of design patterns as elements of reusable object-oriented software. The student is familiar with GOF design patterns.

  Prerequisites and co-requisites

  Object-oriented programming

  Course contents

  Purposes of patterns
  Structures and beaviours of patterns
  Applications of patterns

  Assessment criteria

  Satisfactory

  Student knows best practices and design patterns.

  Good

  Student is able to design and implement programs using best practices and design patterns.

  Excellent

  Student is able to diversely design and implement programs using best practices and design patterns.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT20K-O2

  Seats

  0 - 30

  Teacher(s)

  Simo Silander

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Design of Safe and Reliable Systems TX00DB89-3005 02.08.2021-06.08.2021  3 credits  (ICTSUMMER) + -
  Learning outcomes of the course

  After completion of this course the student will be able to perform an application specific risk analysis, has knowledge of the fundamental defect mechanisms and load-bearing limits of hardware components, the typical error mechanisms in software components and can design a fail-safe technical system for a given purpose, which ensures the required minimum amount of functionality for a safe operation in case of a defect by suitable measures. Methodological competencies: Interdisciplinary thinking, acting and communication.

  Prerequisites and co-requisites

  1. C-Programming fundamentals
  2. (Digital) electronic circuits
  3. Mechatronic basics

  Course contents

  1. Introduction
  2. Learning from accidents
  3. Risk analysis and risk reduction methods
  4. Robust design of hardware and software
  5. Methods for failure tolerance
  6. Safety architectures
  7. Robot competition

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  - Electronic Safety Systems, Josef Börcsök
  - IEC EN 61508 (Functional Safety, Safety Related Systems)

  Planned learning activities and teaching methods

  - lectures
  - group work
  - presentations

  Assessment methods and criteria

  The course assessment is based on
  - active attendance
  - continuous assessment of exercises
  - individual contribution to project
  - short exam at the end of the intensive week
  
  It is highly recommended that students attend all sessions.

  Language of instruction

  English

  Timing

  02.08.2021 - 06.08.2021

  Enrollment date

  03.05.2021 - 31.07.2021

  • 3 credits

  Group(s)

  • ICTSUMMER

  Seats

  0 - 24

  Teacher(s)

  Norbert Jung, Marcel Hasler

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  0-5

  Exam schedule

  Exam on the last day of the intensive week

  International connections

  Course teachers are Prof. Dr. Norbert Jung and Marcel Hasler (M.Sc.) from University of Applied Sciences, Bonn-Rhein-Sieg, Germany.

  Students use of time and load

  Lectures 5x4h
  Home exercises 10h
  Project 30h
  Self study 20h
  Total 80h = 3ECTS

  Location and Time

  2.8.2021 - 6.8.2021 (morning 09:00-13:00)

•     Develop a Mobile Application XX00EM93-3001 25.10.2021-31.12.2021  3 credits + -
  Learning outcomes of the course

  Opintojakson suoritettuaan opiskelija pystyy omatoimisesti rakentamaan selainpohjaisia pelillisiä sovelluksia kännykkään (not translated)

  Course contents

  • Työkalut sovelluskehitykseen
  • HTML ja CSS perusteet
  • JavaScript perusteet
  • Valitun JavaScript kirjaston käyttö
  • Sovelluksen suunnittelu
  • Sovelluksen toteutus ja testaus (not translated)

  Assessment criteria

  Satisfactory

  Kurssin hyväksytty suoritus edellyttää, että opiskelijan rakentama sovellus toimii kännykän selaimella (not translated)

  Further information

  Opintojakso on tarkoitettu Espoon lukiolaisille ja Omnian opiskelijoille. (not translated)

  ---

  Name of lecturer(s)

  Matti Peltoniemi

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 31.12.2021

  Enrollment date

  01.08.2020 - 01.08.2020

  • 3 credits

  Teacher(s)

  Ulla Forsström, Matti Peltoniemi

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Developing Chatbots using Microsoft Bot Framework TT00DJ78-3007 01.01.2022-31.12.2022  6 credits  (ATX22TV) + -
  Learning outcomes of the course

  The goal of this course is for the student to be familiar with Microsoft Bot Framework as one of the widely
  used chatbot frameworks. After passing this course, the student will be able to understand different
  components of the framework and will be able to build intelligent chatbot using LUIS a NLU service by
  Microsoft and connect with different communication channels like Facebook, Website, slack etc. And also,
  will be able to deploy chatbot to production and get an idea about managing bot using Azure services.
  This course is 100% virtual thanks to the comprehensive tutorial videos and content made for this course.
  The student will pass this course after submitting required assignments, quiz, and projects.

  Course contents

  Introduction Part:
  What is a chatbot? - Why use chatbots? - The history of chatbot? - Benefits of chatbots - What are the
  types of chatbots? - How do chatbots work? - Chatbot architecture (NLU services - Frameworks -
  Channels) - How you can build a chatbot? - How to build chatbot without & with coding?
  Intermediate Part:
  Bot Architecture (Microsoft cognitive services - Microsoft Bot Framework - Channels) - Cognitive Services
  (LUIS) - Microsoft Bot Framework (Core Concepts - Design Principles - Patterns)
  Advanced Part:
  Create/Manage your Bot - Test/Deploy Bot - Add Intelligence(LUIS) - Integrate channels(Facebook
  Messenger)

  Assessment criteria

  Satisfactory

  - The student knows how chatbots work.
  - The student knows different types of chatbots.
  - The student can explain the general architecture of chatbots.
  - The student knows different chatbot frameworks.
  - The student knows different options to build chatbots with or without coding.
  - The student knows different NLU services

  Good

  - The student knows Microsoft Bot Framework core concepts.
  - The student knows LUIS core concepts.

  Excellent

  - The student knows different patterns to build chat dialog flows.
  - The student can create, train and test LUIS App.
  - The student can deploy bot using LUIS App and Microsoft Bot framework.
  - The student can deploy Bot with channel integration.
  - The student can design advanced chat flows.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in study environment.

  Planned learning activities and teaching methods

  - Tutorial Videos
  - Assignments
  - Quiz
  - Projects
  - Self-study

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 6 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online in study environment.

  International connections

  N/A

  Students use of time and load

  Lectures = 25h
  Labs = 25h
  Assignments = 35h
  Self-study = 40h
  Quiz = 2h
  Project = 5h
  Total = 132 hours

  Content periodicity

  Assignments 40%
  Quiz 20%
  Project 40%

  Location and Time

  Up to Student her-/himself - course is online (Self-Study) course.

•     Developing Modern Web Platforms (HTML,CSS,JS) TT00CQ83-3009 01.01.2022-31.12.2022  15 credits  (ATX22TV) + -
  Learning outcomes of the course

  The goal of this course is for the student to be familiar with required technologies to develop modern web platforms. After passing this course, the student will be able to select between primary technologies in web designing to work with them, and also develop projects and websites using such technologies. The student will be introduced to HTML as a markup language for describing web documents, and then will be familiar with CSS to apply styles on HTML elements, and finally learn JavaScript as an interpreted language to add dynamic functionalities to web applications. Together, they are among the essential technologies of World Wide Web content production.
  This course is 100% virtual thanks to the comprehensive tutorial videos and content made for this course.
  The student will pass this course after submitting required assignments and project.

  Course contents

  Introduction:
  History of Internet - The advent of World Wide Web - How the web works? - How web can get accessed to? - Common Web Protocols - Solutions for hosting our projects - Hosting > Things to consider - Registering a Domain - Importance of having web developing skills for a software engineer - Web Application vs. Desktop Application - Developing Concerns - The evolution of HTML - Developing Concerns - Responsive Design - Editors - Design > Target your audience - Mockups (Wireframes) - Template > Design - Your website statistics - What is Search Engine Optimization? - Publishing your website - Browsers
  
  HTML:
  Tags or Elements - Page Structure - HTML Tags and Attributes - 3 Musketeers - Body Element - Head Element - The Declaration - View the source - Creating your first HTML page - Working with Text - Working with Lists - Working with Links - Working with Images - Working with Tables - Working with Forms - Extra Markups - Commenting in HTML - ID vs. Class - META Tags - Especial Characters
  
  CSS:
  Understanding CSS - HTML and CSS are BestFriendsForever - How CSS works? - How to insert CSS? - CSS Selectors - CSS Rules Overlapping - CSS Rules Inheritance - Mastering Colors - Styling Text - Working with Fonts and Typefaces - Styling Links - Hover, active, focus - Boxes; Border, Margin, and Padding - Styling Lists, Tables and Forms - Layouts - Working with Images - HTML5 Layout Elements - CSS Frameworks - Introduction to Bootstrap
  
  JavaScript:
  Is JavaScript same as Java? - JavaScript benefits - Say hi to Scripts - Understanding flowcharts for programming - Objects and Properties - Events - Methods - Understanding the Document object - When a Browser meets a Web Page - How HTML-CSS-JS coexist? - Writing your first JavaScript - How to store JS? (Internal vs. External) - Using Objects and Methods - Variables and Data Types - Operators - Functions - This - Using Browser Object Model - Using Document Object Model (DOM) - Working with Global Objects - Comparison Operators - Decisions - Loops - Accessing Elements in DOM - Validation - HTML5 JavaScript APIs - Error Handling and Debugging - Introduction to JavaScript Libraries (EXTRA) - Introduction to jQuery (EXTRA) - Introduction to AngularJS (EXTRA) - Introduction to React.JS (EXTRA)

  Assessment criteria

  Satisfactory

  - The student understands the concept of WWW and how to have his/her website up and running with registering domain and allocating a host plan to it.
  - The student is familiar with common web protocols.
  - The student can properly define web applications and their advantageous over desktop applications.
  - The student understands developers concern for developing websites.
  - The student can select proper tools to develop a website.
  - The student is familiar with the basics of HTML.
  - The student is familiar with the basics of CSS.
  - The student is familiar with the basics of JavaScript

  Good

  - The student understands HTML elements and their attributes.
  - The student is able to apply CSS definitions all possible methods.
  - The student understands the concept of Colors and how to apply them on web pages and the elements inside of them.
  - The student is familiar with CSS Frameworks and has an understanding about Bootstrap and how to apply such library.
  - The student is familiar with accessing different elements in DOM.
  - The student is able to validate data entered in HTML forms using JavaScript.
  - The student is familiar with JavaScript libraries and has an understanding about jQuery, AngularJS, and React.JS

  Excellent

  - The student is able to design and implement web pages that have consistent functionalities, well defined HTML tags, and the proper and advance use of CSS.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Material is in TehcClass environment

  Planned learning activities and teaching methods

  - Tutorial Videos
  - Assignments
  - Quiz
  - Projects
  - Self-study

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 15 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  15 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Up to Student her-/himself.

  International connections

  N/A

  Students use of time and load

  Up to Student - course is online (Self-Study) course.

  Content periodicity

  Up to Student - course is online (Self-Study) course.

  Location and Time

  Up to Student - course is online (Self-Study) course.

•     Development of Safe and Secure Software TX00CK77-3010 23.08.2021-17.10.2021  5 credits  (TVT19-O) + -
  Learning outcomes of the course

  A student knows issues considering secure and safe software, especially in web environment.
  A student knows many different ways to make secure web-applications and protect a web server and he/she can make a safe user database and he/she can make many different security tests for it.

  Prerequisites and co-requisites

  Web Programming skills (JavaScript, PHP)

  Course contents

  - Open Web Applications Security Project OWASP
  - SAMM (Software Assurance Maturity Model)
  - ASVS (OWASP Application Security Verification Standard)
  - OWASP TOP 10 -list
  - network security
  - different vulnerabilities of web applications and how to protect web applications against them.
  - Apache web server, installing and configuring
  - safe programming with different programming languages
  - safe database connection (e.g. MySQL)
  - user databases
  - Google Hacking
  - certificates and https-protocol
  - penetration testing
  - server hardening

  Assessment criteria

  Satisfactory

  The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level.

  Good

  The student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. The student has completed the required learning exercises in good or satisfactory level.

  Excellent

  The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT19-O

  Seats

  0 - 40

  Teacher(s)

  Ilpo Kuivanen

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Digital Self Care Applications and Opportunities TX00CG34-3007 23.08.2021-17.10.2021  5 credits  (TVT19-H) + -
  Learning outcomes of the course

  After completing the course, the student understands drivers that are changing healthcare system, knows digital self-care devices, solutions and services, understands self-care related business, customers and perspectives, and applies learned knowledge.

  Course contents

  ? Healthcare system in transition
  ? Digital self-care ecosystem
  ? Products for diagnostics and care
  ? Digital self-care software and services
  ? Perspectives to technology utilization

  Assessment criteria

  Satisfactory

  Students recognizes some digital self-care devices, solutions and services, and identifies self-care ecosystem and drivers changing healthcare system, and uses learned knowledge.

  Good

  Students recognizes digital self-care devices, solutions and services, and understands self-care ecosystem and drivers changing healthcare system, and applies learned knowledge.

  Excellent

  Students thoroughly recognizes digital self-care devices, solutions and services, and has a high-level understanding of self-care ecosystem and drivers changing healthcare system, and applies learned knowledge in advanced manner.

  ---

  Name of lecturer(s)

  Mikael Soini

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT19-H

  Seats

  0 - 36

  Teacher(s)

  Mikael Soini, Juha Havukumpu

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Digital Signal Processing TX00CQ62-3007 09.08.2021-20.08.2021  5 credits  (ICTSUMMER) + -
  Learning outcomes of the course

  Knowledge and understanding:
  - The students will know the basic properties of digital signal processing systems. They are able to analyze signal processing systems and to understand the background of filter design software.
  Skills:
  - The student is able to use basic signal processing tools for analyzing and modifying existing digital signal processing systems.

  Prerequisites and co-requisites

  Basic mathematics and complex numbers, C programming language

  Course contents

  Core content level:
  Basics of Digital Signal Processing: discrete signals and their properties, properties of sampled linear systems, difference equation, convolution, correlation, analysis of linear discrete-time systems: impulse and step responses, transfer function, frequency response,
  Discrete Fourier Transform (DFT), z-Transform, pole-zero- diagram. basic audio signal processing
  
  Additional content:
  Training material including solved problems are provided.

  Assessment criteria

  Satisfactory

  Student understands the fundamentals of digital signal processing

  Good

  Student can apply digital signal processing methods on solving simple problems.

  Excellent

  Student can apply digital signal processing methods as a part of system development.

  ---

  Mode of delivery

  Distance learning

  Assessment methods and criteria

  Exam of 90 minutes duration held about two weeks after the end of the course.

  Language of instruction

  English

  Timing

  09.08.2021 - 20.08.2021

  Enrollment date

  03.05.2021 - 05.08.2021

  • 5 credits

  Group(s)

  • ICTSUMMER

  Seats

  0 - 50

  Teacher(s)

  Manfred Jungke

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Exam schedule

  Exam of 90 minutes duration held about two weeks after the end of the course.

  International connections

  Course teacher is Prof. Dr. Manfred Jungke from Frankfurt University of Applied Sciences, Germany.

  Location and Time

  9.8.2021 - 20.8.2021 (morning 09:00-13:00)

•     Digital Signal Processing TX00CQ31-3007 23.08.2021-17.10.2021  5 credits  (ICT19-SI-E) + -
  Learning outcomes of the course

  After completion of this course the student will understand the fundamentals of digital signal processing. The student will be familiar with the most common operations involved in digital signal processing chain. The student will understand the importance of sampling operation and its key characteristics, applied to low pass signal but also to a band pass signal.
  
  The student understands fundamentals of linear quantization and quantization signal to noise. The student understands the concepts linear-time-invariant system, difference equation, Z-transform, impulse response, discrete convolution, system stability, and frequency response.
  
  The student can apply these concepts in digital filter (FIR/IIR) implementations.

  Prerequisites and co-requisites

  Programming (any language)

  Course contents

  1. Time and frequency domain.
  2. Analogue and digital signals.
  3. Multiplication vs. Convolution.
  4. Uniform sampling, Shannon.
  6. Sampling error, anti-aliasing filter.
  7. Linear quantization, SQNR.
  8. Digital sequences.
  9. Linear time invariant systems, impulse response, difference equation, convolution.
  10. Time domain response.
  11. Frequency response.
  12. Stability criteria.
  13. Z transform, transfer function H(z), properties.
  14. Digital Filtering.
  15. FIR and IIR implementation, basic method for synthesis.

  Assessment criteria

  Satisfactory

  Student understands fundamentals of linear DSP systems, and is able to utilize existing DSP tools on problem solving.

  Good

  In addition to satisfactory level, the student is able to choose and implement suitable DSP methods for DSP problem solving.

  Excellent

  In addition to good level, the student understands concept of computational complexity of DSP algorithms and is able to analyze complexity of various algorithms.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT19-SI-E

  Seats

  0 - 40

  Teacher(s)

  Jarkko Vuori

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Discrete Mathematics TT00ES93-3003 01.08.2021-31.12.2021  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Discrete Mathematics TT00ES93-3005 18.02.2022-30.12.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi

  Language of instruction

  English

  Timing

  18.02.2022 - 30.12.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Discrete Mathematics TT00ES93-3006 18.02.2022-06.08.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi

  Language of instruction

  English

  Timing

  18.02.2022 - 06.08.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Discrete Mathematics TT00ES93-3009 01.01.2022-31.12.2022  3 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop
  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Discrete Mathematics TT00EM30-3003 01.08.2021-31.12.2021  3 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  Further information

  Self-Study Viope course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% Online Self-Study course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Discrete Mathematics TT00EM30-3007 28.02.2022-06.08.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  Further information

  Self-Study Viope course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% Online Self-Study course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  28.02.2022 - 06.08.2022

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Discrete Mathematics TT00EM30-3010 01.01.2022-31.12.2022  3 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  Further information

  Self-Study Viope course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% Online Self-Study course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Discrete Mathematics TX00CD83-3015 23.08.2021-19.12.2021  5 credits  (TVT20-O) + -
  Learning outcomes of the course

  After completing this course the student will be familiar with the basic concepts and facts in logic, set theory, relations, graphs and combinatorics. The student will have a vision of possible applications. In order to model technological systems and structures the student is able to utilize discrete models.

  Course contents

  1) Logic, theory of sets, relations and functions.
  2) Combinatorics.
  3) Graphs.

  Assessment criteria

  Satisfactory

  1) Logic, theory of sets, relations and functions
  The student is familiar with the concepts, notation and principles associated with proposition and predicate logic, set theory, relations and functions. The student is able to solve simple problems.
  2) Combinatorics
  The student is familiar with combinatorial concepts, notation and principles. The student is able to solve simple problems.
  3) Graphs
  The student is familiar with graph theoretic concepts, notation and principles. The student is able to solve simple problems.

  Good

  1) Logic, theory of sets, relations and functions
  The student has a good command of the concepts, notation and principles associated with proposition and predicate logic, set theory, relations and functions. The student is able to solve fundamental problems.
  2) Combinatorics
  The student has a good command of combinatorial concepts, notation and principles. The student is able to solve fundamental problems.
  3) Graphs
  The student has a good command of graph theoretic concepts, notation and principles. The student is able to solve fundamental problems.

  Excellent

  1) Logic, theory of sets, relations and functions
  The student has a deep understanding of the concepts, notation and principles associated with proposition and predicate logic, set theory, relations and functions. The student is able to solve challenging problems.
  2) Combinatorics
  The student has a deep understanding of combinatorial concepts, notation and principles. The student is able to solve challenging problems.
  3) Graphs
  The student has a deep understanding of graph theoretic concepts, notation and principles. The student is able to solve challenging problems.

  Further information

  Computer exercises will be included.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  01.01.2020 - 01.01.2020

  • 5 credits

  Group(s)

  • TVT20-O

  Seats

  0 - 40

  Teacher(s)

  Jorma Räty

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Discrete Mathematics TT00EM30-3006 03.11.2021-27.02.2022  3 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course the student knows the basic concepts of logic, set theory, relations, and their relationships to applications. He/she can construct and perceive structures in information technology with the aid of models offered by discrete mathematics.

  Course contents

  1. Logic
  2. Set theory
  3. Relations
  4. Funcitons
  5. Nets

  Further information

  Self-Study Viope course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% Online Self-Study course.

  Assessment methods and criteria

  When you have done 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  03.11.2021 - 27.02.2022

  Enrollment date

  01.07.2021 - 01.07.2021

  • 3 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Docker TT00EM54-3003 01.01.2022-31.12.2022  5 credits  (ATX22TV) + -
  Learning outcomes of the course

  The goal of this course is for the student to be familiar with the concept of DevOps and Docker. Students will learn the Advantageous of using CI/CD in software development. Then the student will be fully introduced to Docker as one of the most potent tools for virtualization and cloud systems. After passing this course, the student will be able to design and optimize the software development project delivery. Furthermore, they would be capable of configuring CI/CD pipelines and architecture project's hosting with new cloud systems like Azure.
  
  This course is 100% virtual thanks to the comprehensive interactive material and content prepared for this course.
  
  The student will pass this course after submitting the required quiz and assignments.

  Course contents

  Introduction - History of Docker - Docker Architecture - Install Docker Desktop - Install Docker Server - What is Docker CLI? - Basic Commands - Docker Image - Docker Hub - Docker Container - Docker Registry Docker Hub - Docker Daemon - Docker File – Volumes – Networks - Advance Docker File - Docker Swarm - What is Docker Compose? - Installation of Docker Compose - Docker Compose File - Managing Docker Compose - What is DevOps? - Continuous Integration - Continuous Deployment - Docker and Cloud Computing

  Assessment criteria

  Satisfactory

  - The student can properly install Docker.
  - The student understands the concept of Docker.
  - The student is familiar with the benefits of CI/CD.
  - The student can adequately explain the concept of Image/ Container.
  - The student understands how Docker works.
  - The student can adequately explain cloud computing with Docker.
  - The student can properly install Docker on his/her local computer.
  - The student is familiar with Docker Registry and Docker Hub.

  Good

  - The student can properly create a Docker file.
  - The student can properly use Docker to create an image and run the container.
  - The student can properly work with Docker CLI and run Docker commands.
  - The student can properly inspect a Docker server, such as status and log.
  - The student has a good understanding of Docker architecture.
  - The student is familiar with Volumes and Networks in Docker.
  - The student can run and manage a Docker Compose.

  Excellent

  - The student can adequately create a Docker Compose file.
  - The student knows how to Install Docker Server.
  - The student can push a Docker image to Docker Hub.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in TechClass environment.

  Planned learning activities and teaching methods

  This course is 100% virtual thanks to the comprehensive interactive material and content prepared for this course.
  
  Course includes:
  - Tutorial Videos
  - Exercises
  - Quiz
  - Project
  - Self-study

  Assessment methods and criteria

  Exercises 30%
  Quizzes 20%
  Project 40%
  Essay 10%

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Lectures = 40h
  Assignments = 25h
  Self-study = 40h
  Quiz = 5h
  Project = 20h
  Essay = 5h
  Total = 135 hours

  Content periodicity

  Lectures = 40h
  Assignments = 25h
  Self-study = 40h
  Quiz = 5h
  Project = 20h
  Essay = 5h
  Total = 135 hours

  Location and Time

  Course is 100% online (Self-Study) course in TechClass environment.

•     Embedded Systems Programming TX00CI61-3010 23.08.2021-17.10.2021  5 credits  (ICT19-SI-E) + -
  Learning outcomes of the course

  The course provides knowledge on developing embedded systems on small scale microcontroller. On completion of the course students will know the principles of debugging and running embedded software in simulated and in production environments. Students are able to develop embedded system using C++ language with hardware interface based on given specifications. Additionally students learn to evaluate the need for software engineering tools for embedded systems.

  Course contents

  - Embedded Operating systems for microcontroller
  - Interfacing hardware
  - C++ language
  - Embedded systems in simulated environment
  - Embedded debugging tools and debugging techniques

  Assessment criteria

  Satisfactory

  Students have achieved the course objectives fairly. Students will be able to identify, define and use the course subject area’s concepts and models. The student understands the criteria and principles of the expertise development.

  Good

  Students have achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Students are able to define the course concepts and models and are able to justify the analysis. The student is able to apply their knowledge in leisure, study and work situations. The student understands the importance of expertise in the field of information technology and is able to analyze his/her own expertise.

  Excellent

  Students have achieved the objectives of the course with excellent marks. Students master commendably the course subject area’s concepts and models. Students are able to make justified and fluent analysis and to present concrete development measures. The students are well prepared to apply their knowledge in leisure, study and work situations. Students are able to analyze the information technology sector expertise and the evolvement of their own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT19-SI-E

  Seats

  0 - 40

  Teacher(s)

  Keijo Länsikunnas

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Mathematics TT00EW06-3002 01.08.2021-31.12.2021  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Course contents

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in course environment.

  Planned learning activities and teaching methods

  100% online (self-study) course which can be done in own pace.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Depends on the student's baseline.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  100% online (self-study) course which can be done in own pace. Course environment is Metropolia's Viope.

•     Engineering Mathematics TT00EW06-3003 01.01.2022-31.12.2022  5 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Course contents

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in course environment.

  Planned learning activities and teaching methods

  100% online (self-study) course which can be done in own pace.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Depends on the student's baseline.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  100% online (self-study) course which can be done in own pace. Course environment is Metropolia's Viope.

•     Engineering Mathematics TT00EW06-3004 15.09.2021-31.12.2025  5 credits  (Polkuopinnot_NonStop, ...) + -
  Learning outcomes of the course

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Course contents

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in course environment.

  Planned learning activities and teaching methods

  100% online (self-study) course which can be done in own pace.

  Language of instruction

  Tuition in Finnish

  Timing

  15.09.2021 - 31.12.2025

  • 5 credits

  Group(s)

  • Polkuopinnot_NonStop
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Depends on the student's baseline.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  100% online (self-study) course which can be done in own pace. Course environment is Metropolia's Viope.

•     Engineering Mathematics TT00EM33-3003 01.08.2021-31.12.2021  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  100% online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2021

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TT00EM34-3003 01.08.2021-31.12.2021  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TT00EM33-3008 28.02.2022-06.08.2022  5 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  100% online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  28.02.2022 - 06.08.2022

  • 5 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TT00EM34-3007 28.02.2022-06.08.2022  5 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  28.02.2022 - 06.08.2022

  • 5 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TT00EM33-3011 01.01.2022-31.12.2022  5 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  100% online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TT00EM34-3010 01.01.2022-31.12.2022  5 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TT00EM34-3011 15.09.2021-31.12.2025  5 credits  (Polkuopinnot_NonStop, ...) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  15.09.2021 - 31.12.2025

  • 5 credits

  Group(s)

  • Polkuopinnot_NonStop
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TX00EL15-3003 23.08.2021-19.12.2021  5 credits  (TXK21S1-A) + -
  Learning outcomes of the course

  On completion of the the course, student knows the fundamentals of engineering mathematics and is able to apply them.

  Course contents

  - expressions and equations
  - functions
  - vectors and matrices

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  01.01.2021 - 01.01.2021

  • 5 credits

  Group(s)

  • TXK21S1-A

  Seats

  0 - 30

  Teacher(s)

  Birgitta Nenonen-Andersson

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Mathematics TX00EL15-3004 23.08.2021-19.12.2021  5 credits  (TXK21S1-F) + -
  Learning outcomes of the course

  On completion of the the course, student knows the fundamentals of engineering mathematics and is able to apply them.

  Course contents

  - expressions and equations
  - functions
  - vectors and matrices

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  01.01.2021 - 01.01.2021

  • 5 credits

  Group(s)

  • TXK21S1-F

  Seats

  0 - 30

  Teacher(s)

  Birgitta Nenonen-Andersson

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Mathematics TX00CH61-3008 23.08.2021-17.10.2021  5 credits  (ICT20-SI1) + -
  Learning outcomes of the course

  The student can construct and solve linear models and interpret their results. The students knows the concepts of derivation and integration and is able to apply them into scientific and technical problems.

  Course contents

  - Differentiation
  - Integration
  - Basics of differential equations

  Assessment criteria

  Satisfactory

  The student knows the essential theory and concepts in the field and can utilise them in analysis and solutions of simple problems.

  Good

  The student can combine the knowledge acquired from various fields and, based on that, is able to solve also more demanding mathematical problems.

  Excellent

  In addition to the in-depth management of the course contents, the student shows also capability and motivation to exploit the acquired knowledge into independent development of competence.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT20-SI1

  Seats

  0 - 40

  Teacher(s)

  Timo Salin

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Mathematics TX00CH61-3009 23.08.2021-17.10.2021  5 credits  (ICT20-SI2) + -
  Learning outcomes of the course

  The student can construct and solve linear models and interpret their results. The students knows the concepts of derivation and integration and is able to apply them into scientific and technical problems.

  Course contents

  - Differentiation
  - Integration
  - Basics of differential equations

  Assessment criteria

  Satisfactory

  The student knows the essential theory and concepts in the field and can utilise them in analysis and solutions of simple problems.

  Good

  The student can combine the knowledge acquired from various fields and, based on that, is able to solve also more demanding mathematical problems.

  Excellent

  In addition to the in-depth management of the course contents, the student shows also capability and motivation to exploit the acquired knowledge into independent development of competence.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT20-SI2

  Seats

  0 - 40

  Teacher(s)

  Timo Salin

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Mathematics TT00EM33-3007 03.11.2021-27.02.2022  5 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  100% online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  03.11.2021 - 27.02.2022

  Enrollment date

  31.05.2021 - 29.06.2021

  • 5 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics TT00EM34-3006 03.11.2021-27.02.2022  5 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Course contents

  1. Polynomial functions and equations
  3. Vectors
  4. Analytic geometry
  5. Differential Calculus
  6. Trigonometry
  7. Exponential models and logarithms
  8. Integral Calculus
  9. Statistics and Probability
  10. Number theory
  11. Algorithms in mathematics

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  Tuition in Finnish

  Timing

  03.11.2021 - 27.02.2022

  Enrollment date

  01.07.2021 - 01.07.2021

  • 5 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 3000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  0-5

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself

  Content periodicity

  Up to Student her-/himself

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Engineering Mathematics 2 TT00EW06-3001 01.08.2021-24.10.2021  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Course contents

  Vectors and matrices
  Special matrices, matrix descriptions
  Inverse of a matrix
  Linear group of equations
  Eigenvalues diagonalization
  Fourier transformation
  Laplace transformation
  Z- transformation

  Further information

  Course is 100% Online (Self-Study) course.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in course environment.

  Planned learning activities and teaching methods

  100% online (self-study) course which can be done in own pace.

  Assessment methods and criteria

  After student has done at least 80% of course he/she will get grade pass.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 24.10.2021

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student: Please fill in eform
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Depends on the student's baseline.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  100% online (self-study) course which can be done in own pace. Course environment is Metropolia's Viope.

•     Engineering Physics TX00EL16-3003 23.08.2021-19.12.2021  5 credits  (TXK21S1-A) + -
  Learning outcomes of the course

  After completion of the course, the student knows the basics of engineering physics and can apply them.

  Course contents

  - mechanics
  - electricity
  - oscillations and wave motion

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  01.01.2021 - 01.01.2021

  • 5 credits

  Group(s)

  • TXK21S1-A

  Seats

  0 - 30

  Teacher(s)

  Berit Mannfors

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Physics TX00EL16-3004 23.08.2021-19.12.2021  5 credits  (TXK21S1-F) + -
  Learning outcomes of the course

  After completion of the course, the student knows the basics of engineering physics and can apply them.

  Course contents

  - mechanics
  - electricity
  - oscillations and wave motion

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  01.01.2021 - 01.01.2021

  • 5 credits

  Group(s)

  • TXK21S1-F

  Seats

  0 - 30

  Teacher(s)

  Berit Mannfors

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Physics 1 TT00ER82-3004 01.09.2021-31.12.2021  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing the course, student knows basics of the engineering physics.
  
  Including
  - heat
  - electricity
  - force and motion
  - periodic motion and waves
  - electromagnetism
  - matter and radiation

  Course contents

  - Heat
  - Hlectricity
  - Force and Motion
  - Periodic motion and Waves
  - Electromagnetism
  - Matter and Radiation

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  To get grading pass you have to do at least 80% of this course.

  Language of instruction

  Tuition in Finnish

  Timing

  01.09.2021 - 31.12.2021

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Engineering Physics 1 TT00ER82-3005 31.12.2021-30.12.2022  5 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course, student knows basics of the engineering physics.
  
  Including
  - heat
  - electricity
  - force and motion
  - periodic motion and waves
  - electromagnetism
  - matter and radiation

  Course contents

  - Heat
  - Hlectricity
  - Force and Motion
  - Periodic motion and Waves
  - Electromagnetism
  - Matter and Radiation

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  To get grading pass you have to do at least 80% of this course.

  Language of instruction

  Tuition in Finnish

  Timing

  31.12.2021 - 30.12.2022

  • 5 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Engineering Physics 1 TT00ER82-3006 09.02.2022-06.05.2022  5 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course, student knows basics of the engineering physics.
  
  Including
  - heat
  - electricity
  - force and motion
  - periodic motion and waves
  - electromagnetism
  - matter and radiation

  Course contents

  - Heat
  - Hlectricity
  - Force and Motion
  - Periodic motion and Waves
  - Electromagnetism
  - Matter and Radiation

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  To get grading pass you have to do at least 80% of this course.

  Language of instruction

  Tuition in Finnish

  Timing

  09.02.2022 - 06.05.2022

  • 5 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Engineering Physics 1 TT00ER82-3007 30.04.2022-30.08.2022  5 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After completing the course, student knows basics of the engineering physics.
  
  Including
  - heat
  - electricity
  - force and motion
  - periodic motion and waves
  - electromagnetism
  - matter and radiation

  Course contents

  - Heat
  - Hlectricity
  - Force and Motion
  - Periodic motion and Waves
  - Electromagnetism
  - Matter and Radiation

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  To get grading pass you have to do at least 80% of this course.

  Language of instruction

  Tuition in Finnish

  Timing

  30.04.2022 - 30.08.2022

  • 5 credits

  Group(s)

  • ATX22TV
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Engineering Physics 1 TT00ER82-3011 01.01.2022-31.12.2022  5 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  After completing the course, student knows basics of the engineering physics.
  
  Including
  - heat
  - electricity
  - force and motion
  - periodic motion and waves
  - electromagnetism
  - matter and radiation

  Course contents

  - Heat
  - Hlectricity
  - Force and Motion
  - Periodic motion and Waves
  - Electromagnetism
  - Matter and Radiation

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  To get grading pass you have to do at least 80% of this course.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Engineering Physics 1 TT00ER82-3012 15.09.2021-31.12.2025  5 credits  (Polkuopinnot_NonStop, ...) + -
  Learning outcomes of the course

  After completing the course, student knows basics of the engineering physics.
  
  Including
  - heat
  - electricity
  - force and motion
  - periodic motion and waves
  - electromagnetism
  - matter and radiation

  Course contents

  - Heat
  - Hlectricity
  - Force and Motion
  - Periodic motion and Waves
  - Electromagnetism
  - Matter and Radiation

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  To get grading pass you have to do at least 80% of this course.

  Language of instruction

  Tuition in Finnish

  Timing

  15.09.2021 - 31.12.2025

  • 5 credits

  Group(s)

  • Polkuopinnot_NonStop
  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via Metropolia's Viope environment and it can be done in own pace.

•     Engineering Physics 2 TT00EW22-3001 07.09.2021-31.12.2021  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing the course, the student is able to
  
  - explain the concepts of modern physics and phenomena and solve problems associated with these phenomena
  - identify classical physics and differences between modern physics and understand the flaws of classical physics
  - understand the basics of relativity, about quantum physics, on atomic physics, on statistical physics, on the physics of solid state, on nuclear physics, on particle physics and cosmology

  Prerequisites and co-requisites

  Engineering Physics 1
  Engineering Mathematics 1
  Engineering Mathematics 2

  Course contents

  - Theory of relativity
  - Quantum physics
  - Atomic physics
  - Statistical Physics
  - Solid-state physics
  - Nuclear physics
  - Particle physics
  - Cosmology

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course which can be done in own pace.

  Assessment methods and criteria

  When student has done at least 80% of course he/she get mark pass.

  Language of instruction

  Tuition in Finnish

  Timing

  07.09.2021 - 31.12.2021

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Location and Time

  Course can be done in own pace in Metropolia's Viope environment.

•     Engineering Physics 2 TT00EW22-3002 01.01.2022-31.12.2022  5 credits  (VIOPE_NonStop, ...) + -
  Learning outcomes of the course

  After completing the course, the student is able to
  
  - explain the concepts of modern physics and phenomena and solve problems associated with these phenomena
  - identify classical physics and differences between modern physics and understand the flaws of classical physics
  - understand the basics of relativity, about quantum physics, on atomic physics, on statistical physics, on the physics of solid state, on nuclear physics, on particle physics and cosmology

  Prerequisites and co-requisites

  Engineering Physics 1
  Engineering Mathematics 1
  Engineering Mathematics 2

  Course contents

  - Theory of relativity
  - Quantum physics
  - Atomic physics
  - Statistical Physics
  - Solid-state physics
  - Nuclear physics
  - Particle physics
  - Cosmology

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course which can be done in own pace.

  Assessment methods and criteria

  When student has done at least 80% of course he/she get mark pass.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 5 credits

  Group(s)

  • VIOPE_NonStop
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Location and Time

  Course can be done in own pace in Metropolia's Viope environment.

•     Engineering Physics 2 TT00EW22-3003 01.01.2022-30.04.2022  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing the course, the student is able to
  
  - explain the concepts of modern physics and phenomena and solve problems associated with these phenomena
  - identify classical physics and differences between modern physics and understand the flaws of classical physics
  - understand the basics of relativity, about quantum physics, on atomic physics, on statistical physics, on the physics of solid state, on nuclear physics, on particle physics and cosmology

  Prerequisites and co-requisites

  Engineering Physics 1
  Engineering Mathematics 1
  Engineering Mathematics 2

  Course contents

  - Theory of relativity
  - Quantum physics
  - Atomic physics
  - Statistical Physics
  - Solid-state physics
  - Nuclear physics
  - Particle physics
  - Cosmology

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course which can be done in own pace.

  Assessment methods and criteria

  When student has done at least 80% of course he/she get mark pass.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 30.04.2022

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Location and Time

  Course can be done in own pace in Metropolia's Viope environment.

•     Engineering Physics 2 TT00EW22-3004 01.05.2022-31.08.2022  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  After completing the course, the student is able to
  
  - explain the concepts of modern physics and phenomena and solve problems associated with these phenomena
  - identify classical physics and differences between modern physics and understand the flaws of classical physics
  - understand the basics of relativity, about quantum physics, on atomic physics, on statistical physics, on the physics of solid state, on nuclear physics, on particle physics and cosmology

  Prerequisites and co-requisites

  Engineering Physics 1
  Engineering Mathematics 1
  Engineering Mathematics 2

  Course contents

  - Theory of relativity
  - Quantum physics
  - Atomic physics
  - Statistical Physics
  - Solid-state physics
  - Nuclear physics
  - Particle physics
  - Cosmology

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  100% online (Self-Study) course which can be done in own pace.

  Assessment methods and criteria

  When student has done at least 80% of course he/she get mark pass.

  Language of instruction

  Tuition in Finnish

  Timing

  01.05.2022 - 31.08.2022

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Location and Time

  Course can be done in own pace in Metropolia's Viope environment.

•     Engineering Swedish TX00BP91-3165 23.08.2021-19.12.2021  5 credits  (TVT19K-O) + -
  Learning outcomes of the course

  On completion of the course, the student will possess the written and oral language skills in the second domestic language that are necessary in their professional field, as required by national legislation (352/2003 8§).
  The student will be able to communicate in Swedish in professional contexts both in Finland and in the other Nordic countries, taking into account the cultural and linguistic backgrounds of the communication partners.
  The student will possess oral and written language and communication skills that are at least at the level B1 as defined in the Common European Framework of Reference for Languages. The student will be able to seek information related to his/her own professional field in various sources and convey information both orally and in writing.
  During their studies, the student will have formed a positive and realistic view of his/her language and communicative competence as well as skills and motivation to develop the competence further.

  Prerequisites and co-requisites

  The acquisition of professional language and communication competence in the second domestic language (Swedish) requires the starting level B1.1 as defined by the Common European Framework of Reference for Languages.

  Course contents

  The course content will be tailored according to each Degree Programme or specialisation option.
  The contents of the course focus on field-specific oral and written exercises related to the following themes:
  • self-assessing one’s language and communication skills and developing learning strategies
  • education and career planning
  • organisations, working environments, tasks, processes and tools of the profession
  • field-related texts; increasing and activating the knowledge of technical terminology
  • key interactive communication situations: individual and group communication

  Assessment criteria

  Satisfactory

  In communication situations related to his/her field the student
  • Is able to cope in the most common general and specialised professional communication situations
  • Composes simple, though partly incoherent texts. Language errors may impair understanding but do not prevent the delivery of the message
  • Participates in simple spoken interaction but often needs help from the conversation partner
  • Uses basic general and technical terminology of his/her own field; however, inaccuracy and the influence of other languages may interfere with the delivery of the message.
  • Uses basic grammatical structures in a repetitious manner and partly incorrectly
  • Pronounces words mostly in a manner that can be understood, although the pronunciation deviates from that of the target language. Furthermore, the slow sentence rhythm makes the delivery of the message difficult.

  Good

  In communication situations related to his/her field the student
  • Succeeds relatively well in daily general and specialised professional discourse
  • Composes coherent texts that successfully communicate the intended meaning despite of grammatical errors and insufficient vocabulary
  • Takes initiative in familiar professional communication situations
  • Uses general and basic technical terminology of his/her own field relatively well. Lapses may occur in the choice of words or grammatical structures, but these do not cause misunderstanding
  • Pronounces in a manner that can be understood. Pauses in the sentence rhythm do not cause misunderstandings.

  Excellent

  In communication situations related to his/her field the student
  • Masters even varied and demanding general and specialised professional communication situations
  • Produces clear and detailed texts appropriate for the situation
  • Is an active participant in professional communication situations and allows for the requirements of the situation. Speaks fluently and effortlessly and takes the conversation partner into account
  • Uses technical and general terminology as well as grammatical structures diversely and almost without errors
  • Pronounces clearly, with a natural sentence rhythm
  • Pronounces clearly, with a natural sentence rhythm

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT19K-O

  Seats

  0 - 25

  Teacher(s)

  Anne Pajala

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Engineering Swedish TX00BP91-3167 23.08.2021-17.10.2021  5 credits  (ICT19K-M) + -
  Learning outcomes of the course

  On completion of the course, the student will possess the written and oral language skills in the second domestic language that are necessary in their professional field, as required by national legislation (352/2003 8§).
  The student will be able to communicate in Swedish in professional contexts both in Finland and in the other Nordic countries, taking into account the cultural and linguistic backgrounds of the communication partners.
  The student will possess oral and written language and communication skills that are at least at the level B1 as defined in the Common European Framework of Reference for Languages. The student will be able to seek information related to his/her own professional field in various sources and convey information both orally and in writing.
  During their studies, the student will have formed a positive and realistic view of his/her language and communicative competence as well as skills and motivation to develop the competence further.

  Prerequisites and co-requisites

  The acquisition of professional language and communication competence in the second domestic language (Swedish) requires the starting level B1.1 as defined by the Common European Framework of Reference for Languages.

  Course contents

  The course content will be tailored according to each Degree Programme or specialisation option.
  The contents of the course focus on field-specific oral and written exercises related to the following themes:
  • self-assessing one’s language and communication skills and developing learning strategies
  • education and career planning
  • organisations, working environments, tasks, processes and tools of the profession
  • field-related texts; increasing and activating the knowledge of technical terminology
  • key interactive communication situations: individual and group communication

  Assessment criteria

  Satisfactory

  In communication situations related to his/her field the student
  • Is able to cope in the most common general and specialised professional communication situations
  • Composes simple, though partly incoherent texts. Language errors may impair understanding but do not prevent the delivery of the message
  • Participates in simple spoken interaction but often needs help from the conversation partner
  • Uses basic general and technical terminology of his/her own field; however, inaccuracy and the influence of other languages may interfere with the delivery of the message.
  • Uses basic grammatical structures in a repetitious manner and partly incorrectly
  • Pronounces words mostly in a manner that can be understood, although the pronunciation deviates from that of the target language. Furthermore, the slow sentence rhythm makes the delivery of the message difficult.

  Good

  In communication situations related to his/her field the student
  • Succeeds relatively well in daily general and specialised professional discourse
  • Composes coherent texts that successfully communicate the intended meaning despite of grammatical errors and insufficient vocabulary
  • Takes initiative in familiar professional communication situations
  • Uses general and basic technical terminology of his/her own field relatively well. Lapses may occur in the choice of words or grammatical structures, but these do not cause misunderstanding
  • Pronounces in a manner that can be understood. Pauses in the sentence rhythm do not cause misunderstandings.

  Excellent

  In communication situations related to his/her field the student
  • Masters even varied and demanding general and specialised professional communication situations
  • Produces clear and detailed texts appropriate for the situation
  • Is an active participant in professional communication situations and allows for the requirements of the situation. Speaks fluently and effortlessly and takes the conversation partner into account
  • Uses technical and general terminology as well as grammatical structures diversely and almost without errors
  • Pronounces clearly, with a natural sentence rhythm
  • Pronounces clearly, with a natural sentence rhythm

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 17.10.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • ICT19K-M

  Seats

  0 - 25

  Teacher(s)

  Anne Pajala

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Engineering Swedish TX00BP91-3187 23.08.2021-19.12.2021  5 credits  (TVT19K-O) + -
  Learning outcomes of the course

  On completion of the course, the student will possess the written and oral language skills in the second domestic language that are necessary in their professional field, as required by national legislation (352/2003 8§).
  The student will be able to communicate in Swedish in professional contexts both in Finland and in the other Nordic countries, taking into account the cultural and linguistic backgrounds of the communication partners.
  The student will possess oral and written language and communication skills that are at least at the level B1 as defined in the Common European Framework of Reference for Languages. The student will be able to seek information related to his/her own professional field in various sources and convey information both orally and in writing.
  During their studies, the student will have formed a positive and realistic view of his/her language and communicative competence as well as skills and motivation to develop the competence further.

  Prerequisites and co-requisites

  The acquisition of professional language and communication competence in the second domestic language (Swedish) requires the starting level B1.1 as defined by the Common European Framework of Reference for Languages.

  Course contents

  The course content will be tailored according to each Degree Programme or specialisation option.
  The contents of the course focus on field-specific oral and written exercises related to the following themes:
  • self-assessing one’s language and communication skills and developing learning strategies
  • education and career planning
  • organisations, working environments, tasks, processes and tools of the profession
  • field-related texts; increasing and activating the knowledge of technical terminology
  • key interactive communication situations: individual and group communication

  Assessment criteria

  Satisfactory

  In communication situations related to his/her field the student
  • Is able to cope in the most common general and specialised professional communication situations
  • Composes simple, though partly incoherent texts. Language errors may impair understanding but do not prevent the delivery of the message
  • Participates in simple spoken interaction but often needs help from the conversation partner
  • Uses basic general and technical terminology of his/her own field; however, inaccuracy and the influence of other languages may interfere with the delivery of the message.
  • Uses basic grammatical structures in a repetitious manner and partly incorrectly
  • Pronounces words mostly in a manner that can be understood, although the pronunciation deviates from that of the target language. Furthermore, the slow sentence rhythm makes the delivery of the message difficult.

  Good

  In communication situations related to his/her field the student
  • Succeeds relatively well in daily general and specialised professional discourse
  • Composes coherent texts that successfully communicate the intended meaning despite of grammatical errors and insufficient vocabulary
  • Takes initiative in familiar professional communication situations
  • Uses general and basic technical terminology of his/her own field relatively well. Lapses may occur in the choice of words or grammatical structures, but these do not cause misunderstanding
  • Pronounces in a manner that can be understood. Pauses in the sentence rhythm do not cause misunderstandings.

  Excellent

  In communication situations related to his/her field the student
  • Masters even varied and demanding general and specialised professional communication situations
  • Produces clear and detailed texts appropriate for the situation
  • Is an active participant in professional communication situations and allows for the requirements of the situation. Speaks fluently and effortlessly and takes the conversation partner into account
  • Uses technical and general terminology as well as grammatical structures diversely and almost without errors
  • Pronounces clearly, with a natural sentence rhythm
  • Pronounces clearly, with a natural sentence rhythm

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  23.08.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 22.08.2021

  • 5 credits

  Group(s)

  • TVT19K-O

  Seats

  0 - 25

  Teacher(s)

  Anne Pajala

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Myllypurontie 1

  Evaluation scale

  0-5

•     Engineering Swedish TX00BP91-3191 25.10.2021-19.12.2021  5 credits  (TVT18-PE) + -
  Learning outcomes of the course

  On completion of the course, the student will possess the written and oral language skills in the second domestic language that are necessary in their professional field, as required by national legislation (352/2003 8§).
  The student will be able to communicate in Swedish in professional contexts both in Finland and in the other Nordic countries, taking into account the cultural and linguistic backgrounds of the communication partners.
  The student will possess oral and written language and communication skills that are at least at the level B1 as defined in the Common European Framework of Reference for Languages. The student will be able to seek information related to his/her own professional field in various sources and convey information both orally and in writing.
  During their studies, the student will have formed a positive and realistic view of his/her language and communicative competence as well as skills and motivation to develop the competence further.

  Prerequisites and co-requisites

  The acquisition of professional language and communication competence in the second domestic language (Swedish) requires the starting level B1.1 as defined by the Common European Framework of Reference for Languages.

  Course contents

  The course content will be tailored according to each Degree Programme or specialisation option.
  The contents of the course focus on field-specific oral and written exercises related to the following themes:
  • self-assessing one’s language and communication skills and developing learning strategies
  • education and career planning
  • organisations, working environments, tasks, processes and tools of the profession
  • field-related texts; increasing and activating the knowledge of technical terminology
  • key interactive communication situations: individual and group communication

  Assessment criteria

  Satisfactory

  In communication situations related to his/her field the student
  • Is able to cope in the most common general and specialised professional communication situations
  • Composes simple, though partly incoherent texts. Language errors may impair understanding but do not prevent the delivery of the message
  • Participates in simple spoken interaction but often needs help from the conversation partner
  • Uses basic general and technical terminology of his/her own field; however, inaccuracy and the influence of other languages may interfere with the delivery of the message.
  • Uses basic grammatical structures in a repetitious manner and partly incorrectly
  • Pronounces words mostly in a manner that can be understood, although the pronunciation deviates from that of the target language. Furthermore, the slow sentence rhythm makes the delivery of the message difficult.

  Good

  In communication situations related to his/her field the student
  • Succeeds relatively well in daily general and specialised professional discourse
  • Composes coherent texts that successfully communicate the intended meaning despite of grammatical errors and insufficient vocabulary
  • Takes initiative in familiar professional communication situations
  • Uses general and basic technical terminology of his/her own field relatively well. Lapses may occur in the choice of words or grammatical structures, but these do not cause misunderstanding
  • Pronounces in a manner that can be understood. Pauses in the sentence rhythm do not cause misunderstandings.

  Excellent

  In communication situations related to his/her field the student
  • Masters even varied and demanding general and specialised professional communication situations
  • Produces clear and detailed texts appropriate for the situation
  • Is an active participant in professional communication situations and allows for the requirements of the situation. Speaks fluently and effortlessly and takes the conversation partner into account
  • Uses technical and general terminology as well as grammatical structures diversely and almost without errors
  • Pronounces clearly, with a natural sentence rhythm
  • Pronounces clearly, with a natural sentence rhythm

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  Tuition in Finnish

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  03.05.2021 - 17.10.2021

  • 5 credits

  Group(s)

  • TVT18-PE

  Seats

  0 - 25

  Teacher(s)

  Anne Pajala

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Enterprise Networking, Security and Automation TX00EI87-3001 25.10.2021-19.12.2021  5 credits  (ICT20-SI1) + -
  Learning outcomes of the course

  Enterprise Networking, Security, and Automation describes the architecture, components, operations, and security to scale for large, complex networks, including wide area network (WAN) technologies. The course emphasizes network security concepts and introduces network virtualization and automation. On completion of the course students know how to configure, troubleshoot, and secure enterprise network devices and understand how application programming interfaces (API) and configuration management tools enable network automation.

  Course contents

  OSPF routing protocol
  Security best practices
  Access control lists
  Network Address Translation (NAT)
  Remote access connections
  Scalable network architectures
  Quality of Service (QoS)
  Managing large networks
  Virtualization, Software-defined networking and automation

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT20-SI1

  Seats

  0 - 40

  Teacher(s)

  Marko Uusitalo

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Enterprise Networking, Security and Automation TX00EI87-3002 25.10.2021-19.12.2021  5 credits  (ICT20-SI2) + -
  Learning outcomes of the course

  Enterprise Networking, Security, and Automation describes the architecture, components, operations, and security to scale for large, complex networks, including wide area network (WAN) technologies. The course emphasizes network security concepts and introduces network virtualization and automation. On completion of the course students know how to configure, troubleshoot, and secure enterprise network devices and understand how application programming interfaces (API) and configuration management tools enable network automation.

  Course contents

  OSPF routing protocol
  Security best practices
  Access control lists
  Network Address Translation (NAT)
  Remote access connections
  Scalable network architectures
  Quality of Service (QoS)
  Managing large networks
  Virtualization, Software-defined networking and automation

  Assessment criteria

  Satisfactory

  Student has achieved the course objectives fairly. Student will be able to identify, define and use the course subject area’s concepts and models. Student understands the criteria and principles of the expertise development.

  Good

  Student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. Student is able to define the course concepts and models and is able to justify the analysis. Student is able to apply his/her knowledge in study and work situations. Student understands the importance of expertise in the field of information and communication technology and is able to analyze his/her own expertise.

  Excellent

  Student has achieved the objectives of the course with excellent marks. Student masters commendably the course subject area’s concepts and models. Student is able to make justified and fluent analysis and to present concrete development measures. Student is well prepared to apply his/her knowledge in study and work situations. Student is able to analyze expertise in the information and communication technology sector and the development of his/her own expertise.

  ---

  Mode of delivery

  Face-to-face

  Language of instruction

  English

  Timing

  25.10.2021 - 19.12.2021

  Enrollment date

  24.05.2021 - 31.07.2021

  • 5 credits

  Group(s)

  • ICT20-SI2

  Seats

  0 - 40

  Teacher(s)

  Marko Uusitalo

  Unit, in charge

  School of ICT

  Degree Programme

  Degree Programme in Information Technology, Information and Communication Technology

  Unit location

  Karaportti 2

  Evaluation scale

  0-5

•     Ethical Hacking TT00EN28-3004 01.08.2021-31.07.2022  6 credits  (DiplomaCS) + -
  Learning outcomes of the course

  After the course, student knows how-to exposure to threat vectors and counter measures, address emerging areas of cloud and mobile hacking. Course provides the advanced hacking tools and techniques used by hackers and information security professionals.
  
  Course is
  - Online
  - Self-Study online course

  Course contents

  Introduction to ethical hacking
  Foot printing and reconnaissance
  Scanning networks
  Enumeration
  Sniffing
  System hacking
  Malware threats
  Social engineering
  Denial of service
  Session hijacking
  Hacking web applications
  SQL injection
  Hacking wireless networks
  Hacking web servers
  Hacking mobile platforms
  Evading IDS, Firewalls, and Honeypot
  Cloud computing
  Cryptography

  Further information

  Course material is in English and course is delivered via LabSim -portal.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course and it can be done in own pace.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.07.2022

  • 6 credits

  Group(s)

  • DiplomaCS

  Seats

  0 - 100

  Teacher(s)

  Virve Prami

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Depends on the student's baseline.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is 100% online (Self-Study) course and it can be done in own pace. Study environment is LabSim -portal.

•     Ethical Hacking TT00EN28-3003 01.01.2022-31.07.2023  6 credits  (ATX22TV, ...) + -
  Learning outcomes of the course

  After the course, student knows how-to exposure to threat vectors and counter measures, address emerging areas of cloud and mobile hacking. Course provides the advanced hacking tools and techniques used by hackers and information security professionals.
  
  Course is
  - Online
  - Self-Study online course

  Course contents

  Introduction to ethical hacking
  Foot printing and reconnaissance
  Scanning networks
  Enumeration
  Sniffing
  System hacking
  Malware threats
  Social engineering
  Denial of service
  Session hijacking
  Hacking web applications
  SQL injection
  Hacking wireless networks
  Hacking web servers
  Hacking mobile platforms
  Evading IDS, Firewalls, and Honeypot
  Cloud computing
  Cryptography

  Further information

  Course material is in English and course is delivered via LabSim -portal.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online

  Planned learning activities and teaching methods

  100% online Self-study course. All you need is web browser and working network connection.

  Assessment methods and criteria

  You have two choices for completion.
  
  You can do couple of exercises from each module or you can do the test. This test can be found from the environment.

  Language of instruction

  English

  Timing

  01.01.2022 - 31.07.2023

  • 6 credits

  Group(s)

  • ATX22TV
  • ATX23TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  Course will be offered via Open UAS.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  You have two choices for completion. You can do couple of exercises from each module, and or you can do the test. This test can be found from the environment.

  Work placement(s)

  N/A

  Exam schedule

  Online in LabSim environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via LabSim -environment and timetable is totally up to student. Course can be done in own pace.

•     Ethical Hacking TT00EN28-3005 15.09.2021-31.12.2025  6 credits  (Polkuopinnot_NonStop) + -
  Learning outcomes of the course

  After the course, student knows how-to exposure to threat vectors and counter measures, address emerging areas of cloud and mobile hacking. Course provides the advanced hacking tools and techniques used by hackers and information security professionals.
  
  Course is
  - Online
  - Self-Study online course

  Course contents

  Introduction to ethical hacking
  Foot printing and reconnaissance
  Scanning networks
  Enumeration
  Sniffing
  System hacking
  Malware threats
  Social engineering
  Denial of service
  Session hijacking
  Hacking web applications
  SQL injection
  Hacking wireless networks
  Hacking web servers
  Hacking mobile platforms
  Evading IDS, Firewalls, and Honeypot
  Cloud computing
  Cryptography

  Further information

  Course material is in English and course is delivered via LabSim -portal.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online

  Planned learning activities and teaching methods

  100% online Self-study course. All you need is web browser and working network connection.

  Assessment methods and criteria

  You have two choices for completion.
  
  You can do couple of exercises from each module or you can do the test. This test can be found from the environment.

  Language of instruction

  English

  Timing

  15.09.2021 - 31.12.2025

  • 6 credits

  Group(s)

  • Polkuopinnot_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Virve Prami

  Further information for students

  Course will be offered via Open UAS.

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  You have two choices for completion. You can do couple of exercises from each module, and or you can do the test. This test can be found from the environment.

  Work placement(s)

  N/A

  Exam schedule

  Online in LabSim environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Course is delivered via LabSim -environment and timetable is totally up to student. Course can be done in own pace.

•     Ethics of AI TT00EV08-3002 01.01.2022-31.12.2022  4 credits  (ATX22TV) + -
  Learning outcomes of the course

  Artificial intelligence has rapidly progressed in the past decade. This progress has caused AI to become an inseparable part of everybody's lives. Therefore, we must be aware of AI models' limitations as they begin to make important decisions for us. This course will first review the philosophy of ethics and why ethical decision-making is hard. Then it will explore the ethical aspects of AI and discuss each of these aspects as an ethical problem in each chapter. Finally, at the end of each chapter, it suggests some ideas that can address these problems. After passing this course, the student will learn about AI ethics and become familiar with the concepts of disinformation, privacy, bias and fairness, accountability, and the impact of AI on these concepts.

  Course contents

  1. Introduction:
  What is AI? – What is Ethics? – The Trolley Problem – What is AI Ethics? – AI Ethics Framework
  
  2. Disinformation:
  AI and Disinformation – Deep Fakes – How to Deal with AI-enabled Disinformation?
  
  3. Privacy and Surveillance:
  Human Right to Privacy – AI and Threats to Privacy – Impact of AI on the Surveillance World – How to Overcome the Threats
  
  4. Bias and Fairness:
  Definitions of Bias – Different Types of Bias in AI – Fairness – Fairness in AI and Machine Learning
  
  5. Accountability:
  What is Accountability? – Algorithms and Accountability – Responsible AI
  
  6. Ethics of AI in Practice:
  Ethics as Doing – Next Steps
  
  7. Final Tasks
  Project – Self-study Essay

  Assessment criteria

  Satisfactory

  - The student is familiar with the ethics of AI.
  - The student is familiar with the hardness of ethical decision-making.
  - The student is familiar with the impact of AI-generated disinformation.
  - The student is familiar with the concept of deepfake.
  - The student is familiar with the concept of privacy.
  - The student is familiar with the concept of bias.

  Good

  - The student knows about the philosophy of ethics and why it is important
  - The student completely knows about the limitation of AI and Its threads.
  - The student knows about the impact of AI on detecting and generating disinformation.
  - The student is familiar Impact of AI on Surveillance and the way we can stand against its threads.
  - The student knows the fairness and different types of bias in AI
  - The student is familiar with the concept of accountability in AI
  - The student is familiar with how AI ethics is used in practice.
  - The student is familiar with AI transparency.

  Excellent

  - The student completely understands why AI can be a double-edged sword when comes to disinformation generation.
  - The student knows his/her rights to privacy
  - The student knows how to overcome the problem of AI-based surveillance systems.
  - The student understands the difference between equality and equity.
  - The student knows about the responsible AI framework.
  - The student knows how AI ethics can be used in practice.
  - The student knows about AI transparency.

  Further information

  Course is for Open UAS Student.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Lecture slides, tutorial videos, quizzes, exercises, project.

  Planned learning activities and teaching methods

  This course is 100% virtual thanks to the comprehensive tutorial videos and content prepared for this course.
  
  The student will pass this course after submitting the required quiz, assignments, and the final project.

  Assessment methods and criteria

  Exercises 50%
  Quizzes 25%
  Project 25%

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 4 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Further information for students

  Course is for Open UAS Students.
  
  Enrolments via hakija työpöytä https://hakija.oma.metropolia.fi/

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  4 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Lectures = 30h
  Exercises = 30h
  Self-study = 20h
  Quizzes = 5h
  Project = 15h
  Total = 100 hours

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  100% online Self-Study course which can be done in own pace.
  
  Study environment is TechClass -portal.

•     Excel Advanced TT00CQ56-3008 01.08.2021-31.12.2021  3 credits  (ATX21TV) + -
  Learning outcomes of the course

  Kurssilla syvennetään muun muassa funktioiden käyttöä ja suodatusta sekä tutustutaan pivot-taulukoihin. Kurssi on tarkoitettu ohjelmaa toistuvasti käyttävälle, joka haluaa päästä eteenpäin ohjelman laajojen ominaisuuksien hyödyntämisessä tehokkaasti. Kurssi edellyttää vähintään Excel-perusteet -kurssin tietoja ja taitoja sekä käyttökokemusta. (not translated)

  Course contents

  Kurssilla syvennetään muun muassa funktioiden käyttöä ja suodatusta sekä tutustutaan pivot-taulukoihin. Kurssi on tarkoitettu ohjelmaa toistuvasti käyttävälle, joka haluaa päästä eteenpäin ohjelman laajojen ominaisuuksien hyödyntämisessä tehokkaasti. Kurssi edellyttää vähintään Excel-perusteet -kurssin tietoja ja taitoja sekä käyttökokemusta. (not translated)

  Assessment criteria

  Satisfactory

  Student knows how to use Excel with help from the instructor: advanced functions, analysis

  Good

  Student knows how to use Excel at advanced level: advanced functions, analysis

  Excellent

  Student knows how to apply Excel in very extend problems, and can provide solutions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  Can be find in study environment.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • ATX21TV

  Seats

  0 - 1000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Excel Advanced TT00CQ56-3010 01.01.2022-31.07.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  Kurssilla syvennetään muun muassa funktioiden käyttöä ja suodatusta sekä tutustutaan pivot-taulukoihin. Kurssi on tarkoitettu ohjelmaa toistuvasti käyttävälle, joka haluaa päästä eteenpäin ohjelman laajojen ominaisuuksien hyödyntämisessä tehokkaasti. Kurssi edellyttää vähintään Excel-perusteet -kurssin tietoja ja taitoja sekä käyttökokemusta. (not translated)

  Course contents

  Kurssilla syvennetään muun muassa funktioiden käyttöä ja suodatusta sekä tutustutaan pivot-taulukoihin. Kurssi on tarkoitettu ohjelmaa toistuvasti käyttävälle, joka haluaa päästä eteenpäin ohjelman laajojen ominaisuuksien hyödyntämisessä tehokkaasti. Kurssi edellyttää vähintään Excel-perusteet -kurssin tietoja ja taitoja sekä käyttökokemusta. (not translated)

  Assessment criteria

  Satisfactory

  Student knows how to use Excel with help from the instructor: advanced functions, analysis

  Good

  Student knows how to use Excel at advanced level: advanced functions, analysis

  Excellent

  Student knows how to apply Excel in very extend problems, and can provide solutions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  Can be find in study environment.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.07.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Excel Advanced TT00CQ56-3012 01.01.2022-31.12.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  Kurssilla syvennetään muun muassa funktioiden käyttöä ja suodatusta sekä tutustutaan pivot-taulukoihin. Kurssi on tarkoitettu ohjelmaa toistuvasti käyttävälle, joka haluaa päästä eteenpäin ohjelman laajojen ominaisuuksien hyödyntämisessä tehokkaasti. Kurssi edellyttää vähintään Excel-perusteet -kurssin tietoja ja taitoja sekä käyttökokemusta. (not translated)

  Course contents

  Kurssilla syvennetään muun muassa funktioiden käyttöä ja suodatusta sekä tutustutaan pivot-taulukoihin. Kurssi on tarkoitettu ohjelmaa toistuvasti käyttävälle, joka haluaa päästä eteenpäin ohjelman laajojen ominaisuuksien hyödyntämisessä tehokkaasti. Kurssi edellyttää vähintään Excel-perusteet -kurssin tietoja ja taitoja sekä käyttökokemusta. (not translated)

  Assessment criteria

  Satisfactory

  Student knows how to use Excel with help from the instructor: advanced functions, analysis

  Good

  Student knows how to use Excel at advanced level: advanced functions, analysis

  Excellent

  Student knows how to apply Excel in very extend problems, and can provide solutions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  Can be find in study environment.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Excel Basics TT00CQ57-3008 01.08.2021-31.12.2021  3 credits  (ATX21TV) + -
  Learning outcomes of the course

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Course contents

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Assessment criteria

  Satisfactory

  Student knows how to use Excel in Basic level: user interface, basic functions

  Good

  Student knows how to use Excel at Good level (basics): user interface, basic functions

  Excellent

  Student knows how to use Excel at Excellent level (basics): user interface, basic functions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course,

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • ATX21TV

  Seats

  0 - 5000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     Excel Basics TT00CQ55-3008 01.08.2021-31.12.2021  3 credits  (ATX21TV) + -
  Learning outcomes of the course

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Course contents

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Assessment criteria

  Satisfactory

  Student knows how to use Excel in Basic level: user interface, basic functions

  Good

  Student knows how to use Excel at Good level (basics): user interface, basic functions

  Excellent

  Student knows how to use Excel at Excellent level (basics): user interface, basic functions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Language of instruction

  Tuition in Finnish

  Timing

  01.08.2021 - 31.12.2021

  • 3 credits

  Group(s)

  • ATX21TV

  Seats

  0 - 1000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Excel Basics TT00CQ57-3011 01.01.2022-31.07.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Course contents

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Assessment criteria

  Satisfactory

  Student knows how to use Excel in Basic level: user interface, basic functions

  Good

  Student knows how to use Excel at Good level (basics): user interface, basic functions

  Excellent

  Student knows how to use Excel at Excellent level (basics): user interface, basic functions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course,

  Language of instruction

  English

  Timing

  01.01.2022 - 31.07.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     Excel Basics TT00CQ55-3010 01.01.2022-31.07.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Course contents

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Assessment criteria

  Satisfactory

  Student knows how to use Excel in Basic level: user interface, basic functions

  Good

  Student knows how to use Excel at Good level (basics): user interface, basic functions

  Excellent

  Student knows how to use Excel at Excellent level (basics): user interface, basic functions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.07.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Excel Basics TT00CQ57-3013 01.01.2022-31.12.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Course contents

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Assessment criteria

  Satisfactory

  Student knows how to use Excel in Basic level: user interface, basic functions

  Good

  Student knows how to use Excel at Good level (basics): user interface, basic functions

  Excellent

  Student knows how to use Excel at Excellent level (basics): user interface, basic functions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course,

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 5000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find in study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Up to Student her-/himself.

•     Excel Basics TT00CQ55-3012 01.01.2022-31.12.2022  3 credits  (ATX22TV) + -
  Learning outcomes of the course

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Course contents

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Assessment criteria

  Satisfactory

  Student knows how to use Excel in Basic level: user interface, basic functions

  Good

  Student knows how to use Excel at Good level (basics): user interface, basic functions

  Excellent

  Student knows how to use Excel at Excellent level (basics): user interface, basic functions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Language of instruction

  Tuition in Finnish

  Timing

  01.01.2022 - 31.12.2022

  • 3 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Excel Basics TT00CQ55-3013 15.09.2021-31.12.2025  3 credits  (Polkuopinnot_NonStop) + -
  Learning outcomes of the course

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Course contents

  Excel is included in the Microsoft Office suite of applications. Spreadsheets present tables of values arranged in rows and columns that can be manipulated mathematically using both basic and complex arithmetic operations and functions.
  
  In addition to its standard spreadsheet features, Excel also offers programming support via Microsoft's Visual Basic for Applications (VBA), the ability to access data from external sources via Microsoft’s Dynamic Data Exchange (DDE), and extensive graphing and charting capabilities.

  Assessment criteria

  Satisfactory

  Student knows how to use Excel in Basic level: user interface, basic functions

  Good

  Student knows how to use Excel at Good level (basics): user interface, basic functions

  Excellent

  Student knows how to use Excel at Excellent level (basics): user interface, basic functions

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Can be find on study environment.

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Language of instruction

  Tuition in Finnish

  Timing

  15.09.2021 - 31.12.2025

  • 3 credits

  Group(s)

  • Polkuopinnot_NonStop

  Seats

  0 - 5000

  Teacher(s)

  Tapio Wikström

  Further information for students

  ENROLLING
  Open UAS Student: Please fill in eform
  Metropolia's Degree Student: please sent e-mail to contact person Tapio Wikström

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  3 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Can be find on study environment.

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.

  Location and Time

  Because course is 100% online (Self-Study) course, study place and timetable is up to Student her-/himself.

•     Exploratory Data Analysis with Python TT00EU30-3003 01.01.2022-31.12.2022  10 credits  (ATX22TV) + -
  Learning outcomes of the course

  Exploratory Data Analysis (EDA) is a combination of multiple techniques that extract valuable insights and meaningful information from the data. The main aim of EDA is to investigate datasets to reveal the underlying structures, challenges, and opportunities of data without attempting to apply any machine learning model. This course will introduce the student to the practical knowledge and the main pillars of EDA including data exploration, data preparation, data visualization, data relationships and data clustering using Python programming language. Apart from the intuitions, the student will get familiar with how EDA steps are performed by various Python libraries such as NumPy, Pandas, and Matplotlib. After passing this course, the student will be prepared to enter the fantastic world of data analysis towards amazing job positions in the industry.
  
  This course is 100% virtual, thanks to figures and content prepared for this course.

  Prerequisites and co-requisites

  Introduction to Python for Data Science

  Course contents

  1. Introduction:
  Introduction to Data Science – Data Science Workflow – Data – Sources of Data – What is Exploratory Data Analysis? – Python Libraries for EDA
  
  2. Describing Data:
  Introduction – Observations and Variables – Categorical Variables – Continuous Variables – Central Tendency – Data Variability – Data Distributions
  
  3. Importing Data:
  Introduction – Vector and Matrix – NumPy Arrays – Working with NumPy Arrays – Loading Data with NumPy – Pandas Series – Working with Series – Pandas DataFrame – Working with DataFrame – Loading Data with Pandas
  
  4. Data Exploration:
  Extracting Descriptive Statistics – Extracting Descriptive Statistics: Preliminaries – Extracting Descriptive Statistics: Implementation – Mathematical Operations on DataFrame – Applying Functions to DataFrame – Querying a DataFrame – Filtering Data – Groupby – Identifying Unique and Missing Values – Cross Tabulation
  
  5. Data Visualization:
  Univariate Analysis – Histogram – Frequency Polygons – Boxplot – Bar Chart – Pie Chart- Multivariate Analysis – Plot – Subplot – Scatter Plot – Bubble Chart
  
  6. Data Preparation:
  Introduction – Incorrect Values and Categories – Feature Engineering: Creating New Features –Outlier Detection: Univariant –Outlier Detection: Multivariant – Removing Missing Values – Imputing Missing Values: Constant Imputation – Imputing Missing Values: K-NN Imputation – Feature Encoding: Label Encoding – Feature Encoding: One-Hot Encoding – Feature Scaling: Normalization – Feature Scaling: Standardization
  
  7. Data Relationships:
  Introduction – Covariance Matrix – Heatmap of Covariance Matrix – Correlation – Non-linear Relationship – Hypothesis Testing
  
  8. Identifying and Understanding Groups
  Introduction – Clustering – Association Rules – Hierarchical Clustering – K-Means Clustering
  
  9. Next Steps:
  What’s More? – EDA for Text Data – Model Development and Evaluation
  
  10. Final Tasks:
  Self-study Essay – Project

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  Mode of delivery

  40% Face-to-face, 60% Distance learning

  Recommended or required reading

  Lecture slides, quizzes, exercises

  Planned learning activities and teaching methods

  - Exercise
  - Quiz
  - Project
  - Self-study

  Assessment methods and criteria

  Exercise 20%
  Quiz 30%
  Project 30%
  Essay 20%

  Language of instruction

  English

  Timing

  01.01.2022 - 31.12.2022

  • 10 credits

  Group(s)

  • ATX22TV

  Seats

  0 - 1000

  Teacher(s)

  Virve Prami

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  N/A

  International connections

  N/A

  Students use of time and load

  Lectures = 70h
  Exercises = 20h
  Self-study = 40h
  Quizzes = 15h
  Project = 45h
  Total = 190 hours

  Location and Time

  Online TechClass portal.

•     Exploratory Data Analysis with Python TT00EV98-3001 01.08.2021-31.07.2022  6 credits  (DiplomaDA, ...) + -
  Learning outcomes of the course

  Exploratory Data Analysis (EDA) is a combination of multiple techniques that extract valuable insights and meaningful information from the data. The main aim of EDA is to investigate datasets to reveal the underlying structures, challenges, and opportunities of data without attempting to apply any machine learning model. This course will introduce the student to the practical knowledge and the main pillars of EDA including data exploration, data preparation, data visualization, data relationships and data clustering using Python programming language. Apart from the intuitions, the student will get familiar with how EDA steps are performed by various Python libraries such as NumPy, Pandas, and Matplotlib. After passing this course, the student will be prepared to enter the fantastic world of data analysis towards amazing job positions in the industry.

  Course contents

  1. Introduction:
  Introduction to Data Science – Data Science Workflow – Data – Sources of Data – What is Exploratory Data Analysis? – Python Libraries for EDA
  
  2. Describing Data:
  Introduction – Observations and Variables – Categorical Variables – Continuous Variables – Central Tendency – Data Variability – Data Distributions
  
  3. Importing Data:
  Introduction – Vector and Matrix – NumPy Arrays – Working with NumPy Arrays – Loading Data with NumPy – Pandas Series – Working with Series – Pandas DataFrame – Working with DataFrame – Loading Data with Pandas
  
  4. Data Exploration:
  Extracting Descriptive Statistics – Extracting Descriptive Statistics: Preliminaries – Extracting Descriptive Statistics: Implementation – Mathematical Operations on DataFrame – Applying Functions to DataFrame – Querying a DataFrame – Filtering Data – Groupby – Identifying Unique and Missing Values – Cross Tabulation
  
  5. Data Visualization:
  Univariate Analysis – Histogram – Frequency Polygons – Boxplot – Bar Chart – Pie Chart- Multivariate Analysis – Plot – Subplot – Scatter Plot – Bubble Chart
  
  6. Data Preparation:
  Introduction – Incorrect Values and Categories – Feature Engineering: Creating New Features –Outlier Detection: Univariant –Outlier Detection: Multivariant – Removing Missing Values – Imputing Missing Values: Constant Imputation – Imputing Missing Values: K-NN Imputation – Feature Encoding: Label Encoding – Feature Encoding: One-Hot Encoding – Feature Scaling: Normalization – Feature Scaling: Standardization
  
  7. Data Relationships:
  Introduction – Covariance Matrix – Heatmap of Covariance Matrix – Correlation – Non-linear Relationship – Hypothesis Testing
  
  8. Identifying and Understanding Groups
  Introduction – Clustering – Association Rules – Hierarchical Clustering – K-Means Clustering
  
  9. Next Steps:
  What’s More? – EDA for Text Data – Model Development and Evaluation
  
  10. Final Tasks:
  Self-study Essay – Project

  Further information

  Course is only for Diploma in Machine & Deep Learning students.

  ---

  Name of lecturer(s)

  Janne Salonen

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online in TechClass -portal.

  Planned learning activities and teaching methods

  Course is 100% online (Self-Study) course.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.07.2022

  • 6 credits

  Group(s)

  • DiplomaDA
  • DiplomaMD

  Teacher(s)

  Virve Prami

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  6 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online.

  International connections

  N/A

  Students use of time and load

  Up to student her-/himself.

  Content periodicity

  Up to student her-/himself.

  Location and Time

  Course is 100% online (Self-Study) course and study environment is TechClass -portal.

•     Expressions and Equations TT00ES95-3003 01.08.2021-31.12.2021  5 credits  (VIOPE_NonStop) + -
  Learning outcomes of the course

  The student is able to perceive the meaning and interpretation of mathematical expressions. The student knows how to use the Cartesian coordinate system to visualize pairs of numbers and how to plot elementary functions. The student has a clear view of the characteristic properties of the graphs of most important elementary functions.
  -----
  The student is able to perform calculations with integers, fractions and decimal numbers. The student can simplify symbolic expressions composed of basic mathematical operations. The student can plot elementary functions. The student can solve for the angles of a given triangle.
  The student is able to solve linear and quadratic equations, pairs of linear equations and most common types of equations containing roots, logarithms or exponentials.

  Course contents

  Integers, basic algebraic operations and their rules. Fractions and calculations with fractions. Using letters as symbols of numbers. Basic rules of manipulating expressions that contain symbols and numbers. Basic rules for simplifying mathematical expressions. Decimal numbers and accuracy of calculations with decimal numbers. Roots and fractional powers. Solving linear equations and pairs of linear equations. Solving simple equations containing roots. Coordinate system, straight line, parabola and other basic functions. Direct and inverse proportionality. Trigonometric functions solving the right angle. Exponential and logarithmic functions and related simple equations.

  Further information

  Course prepares for UAS studies: The goal is to develop mathematical skills.
  
  Course is delivered via Metropolia's Viope environment and it's 100% online (Self-Study) course.

  ---

  Mode of delivery

  Distance learning

  Recommended or required reading

  Online

  Planned learning activities and teaching methods

  100% online (Self-Study) course.

  Assessment methods and criteria

  When you have done at least 80% of tasks, please send email to viopesupport@metropolia.fi.

  Language of instruction

  English

  Timing

  01.08.2021 - 31.12.2021

  • 5 credits

  Group(s)

  • VIOPE_NonStop

  Seats

  0 - 1000

  Teacher(s)

  Mika Hyyryläinen

  Further information for students

  ENROLLING
  Open UAS and CampusOnline Student via https://hakija.oma.metropolia.fi/
  
  Metropolia's Degree Student: https://vw4.viope.com/login?org=metropolia
  - Register to system -> Click the link “Enroll on the course”
  - Choose any course of (NonStop).
  - Fill the others fields

  Unit, in charge

  School of ICT

  Degree Programme

  Information and Communication Technology

  Unit location

  Karaportti 2

  Virtual proportion

  5 credits

  Evaluation scale

  Hyväksytty/Hylätty

  Completion alternatives

  N/A

  Work placement(s)

  N/A

  Exam schedule

  Online

  International connections

  N/A

  Students use of time and load

  Up to Student her-/himself.

  Content periodicity

  Up to Student her-/himself.