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Data Analysis with Python (10 cr)

Code: TT00EX21-3001

General information


Timing

01.01.2024 - 31.12.2027

Number of ECTS credits allocated

10 op

Virtual portion

10 op

Mode of delivery

Distance learning

Unit

School of ICT

Campus

Karaportti 2

Teaching languages

  • English

Seats

0 - 10000

Degree programmes

  • Degree Programme in Information Technology

Teachers

  • Janne Salonen

Groups

  • IT_path_180_ects
    Information Technology, Open path 180 ECTS

Objective

Learning outcomes of the course: After completing the course, student will learn the fundamentals of data analysis with Python. Student will know how to read data from sources like CSVs and SQL, and how to use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.

Content

- ES6
- Regular Expressions
- Debugging
- Basic Data Structures
- Basic Algorithm Scripting
- Object Oriented Programming
- Functional Programming
- Intermediate Algorithm Scripting

Location and time

Course is 100% online (self-study) course which can be done in own pace. Study environments are Metropolia's Viope and Moodle.

Materials

Online in study environments Metropolia's Viope and Moodle.

Teaching methods

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

Employer connections

N/A

Exam schedules

Online.

International connections

N/A

Completion alternatives

N/A

Student workload

Depends on the student's baseline.

Content scheduling

Up to student her-/himself.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, satisfactory (1)

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.

Assessment criteria, good (3)

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 and communication technology and is able to analyze his/her own expertise.

Assessment criteria, excellent (5)

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 and communication technology sector expertise and the development of their own expertise

Assessment criteria, approved/failed

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.

Assessment methods and criteria

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.