Data/ML Engineering (4 cr)
Code: TX00GB41-3002
General information
- Timing
-
12.05.2025 - 05.09.2025
The implementation has not yet started.
- Number of ECTS credits allocated
- 4 cr
- Mode of delivery
- On-campus
- Unit
- School of ICT and Industrial Management
- Campus
- Karaportti 2
- Teaching languages
- English
- Degree programmes
- Information and Communication Technology
- Teachers
- Tino Kankkunen
- Minna Kivihalme
- Groups
-
DATAINTEL_JOTPAData Intelligence Launchpad - Jotpa hankinta
- Course
- TX00GB41
Objective
This course introduces participants to the application of selected tools for data analytics, artificial intelligence (AI), and machine learning (ML). Participants are required to have prior knowledge of cloud services, data analytics, and AI (through previous program modules or equivalent knowledge). Basic programming skills (Python) and familiarity with SQL are highly recommended. The course content is designed for software developers or professionals in similar advanced ICT roles, as well as recent graduates with a bachelor-level degree in the field.
Knowledge:
• Understand the key principles of data storage, data analytics, and machine learning, as well as their significance in modern software development.
Skills:
• Be able to independently apply data analytics tools and methods for data collection, preprocessing, analysis, and visualization using selected tools.
Responsibility and Independence:
• Understand the ethical and societal impacts of data analytics and artificial intelligence and be able to account for them in professional work.
Content
This course introduces participants to the application of selected tools for data analytics, artificial intelligence (AI), and machine learning (ML). Participants are required to have prior knowledge of cloud services, data analytics, and AI (through previous program modules or equivalent knowledge). Basic programming skills (Python) and familiarity with SQL are highly recommended. The course content is designed for software developers or professionals in similar advanced ICT roles, as well as recent graduates with a bachelor-level degree in the field.
Further information
During the course, there will be a summer break in teaching from June 16 to August 8, 2025. Course content will be available for the students during the summer break.
Evaluation scale
0-5
Further information
During the course, there will be a summer break in teaching from June 16 to August 8, 2025. Course content will be available for the students during the summer break.
Objective
This course introduces participants to the application of selected tools for data analytics, artificial intelligence (AI), and machine learning (ML). Participants are required to have prior knowledge of cloud services, data analytics, and AI (through previous program modules or equivalent knowledge). Basic programming skills (Python) and familiarity with SQL are highly recommended. The course content is designed for software developers or professionals in similar advanced ICT roles, as well as recent graduates with a bachelor-level degree in the field.
Knowledge:
• Understand the key principles of data storage, data analytics, and machine learning, as well as their significance in modern software development.
Skills:
• Be able to independently apply data analytics tools and methods for data collection, preprocessing, analysis, and visualization using selected tools.
Responsibility and Independence:
• Understand the ethical and societal impacts of data analytics and artificial intelligence and be able to account for them in professional work.
Content
This course introduces participants to the application of selected tools for data analytics, artificial intelligence (AI), and machine learning (ML). Participants are required to have prior knowledge of cloud services, data analytics, and AI (through previous program modules or equivalent knowledge). Basic programming skills (Python) and familiarity with SQL are highly recommended. The course content is designed for software developers or professionals in similar advanced ICT roles, as well as recent graduates with a bachelor-level degree in the field.
Further information
During the course, there will be a summer break in teaching from June 16 to August 8, 2025. Course content will be available for the students during the summer break.
Accomplishment methods
• The role of Data Engineer
• Building data analytics solutions using Fabric-tools
• Implementing a data analytics solution
• Working with Data Warehouses
• Implementing a Data Lakehouse analytics solution
• Govern data across an enterprise
• Case company example