Master of Business Administration, Data Engineering and AI: YDATTS24
Code: YDATTS24
Development
Studies include a variety of theoretical and laboratory work on contact teaching days, as well as online studies, exercises, projects, and internships as distance learning.
Further information
The objectives for skill levels in a master’s degree are based on the legislation concerning universities of applied sciences and the European Qualification Framework (EQF). The level corresponding to a master’s degree is level 7. The study evaluation criteria are described in the implementation plan of each course. Criteria are varying depending on different objectives, contents, and implementation models.
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Show study timings by semester, study year or period
| Code | Name | Credits (cr) | 2024-2025 | 2025-2026 | Autumn 2024 | Spring 2025 | Autumn 2025 | Spring 2026 | 1. / 2024 | 2. / 2024 | 3. / 2025 | 4. / 2025 | 5. / 2025 | 1. / 2025 | 2. / 2025 | 3. / 2026 | 4. / 2026 | 5. / 2026 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
CORE COMPETENCE
(Choose all) |
40 | |||||||||||||||||
| YDATTS24-1001 |
Planning for the Future
(Choose all) |
10 | ||||||||||||||||
| MS00BP40 | Future Operating Environments | 5 | 5 | 5 | 2.5 | 2.5 | ||||||||||||
| MS00BP16 | Research and Development Methods | 5 | 5 | 5 | 2.5 | 2.5 | ||||||||||||
| YDATTS24-1002 |
Basics of Data Engineering & AI
(Choose all) |
10 | ||||||||||||||||
| MS00CN43 | Introduction to Data Engineering and AI Technologies | 5 | 5 | 5 | 2.5 | 2.5 | ||||||||||||
| MS00CN44 | Introduction to Cloud Technologies and Security | 5 | 5 | 5 | 2.5 | 2.5 | ||||||||||||
| YDATTS24-1003 |
Data Engineering
(Choose all) |
10 | ||||||||||||||||
| MS00CN45 | MLOps | 5 | 5 | 5 | 1.7 | 1.7 | 1.7 | |||||||||||
| MS00CN46 | Data Engineering project | 5 | 5 | 5 | 1.7 | 1.7 | 1.7 | |||||||||||
| YDATTS24-1004 |
Artificial Intelligence
(Choose all) |
10 | ||||||||||||||||
| MS00CN47 | Components and Application of Artificial Intelligence | 5 | 5 | 5 | 1.7 | 1.7 | 1.7 | |||||||||||
| MS00CN48 | AI project | 5 | 5 | 5 | 1.7 | 1.7 | 1.7 | |||||||||||
|
COMPLEMENTARY COMPETENCE
(Choose 20) |
20 | |||||||||||||||||
| YDATTS24-1005 |
Optional Studies
(Choose ects: 20) |
20 | 20 | 10 | 10 | 5 | 5 | 3.3 | 3.3 | 3.3 | ||||||||
|
MASTER'S THESIS
(Choose all) |
30 | |||||||||||||||||
| MS00BP41 | Master's Thesis | 30 | 5 | 25 | 5 | 10 | 15 | 1.7 | 1.7 | 1.7 | 5 | 5 | 5 | 5 | 5 | |||
| Total | 90 | 45 | 25 | 20 | 25 | 10 | 15 | 10 | 10 | 8.47 | 8.47 | 8.47 | 5 | 5 | 5 | 5 | 5 |
Due to the timing of optional and elective courses, credit accumulation per semester / academic year may vary.
| Code | Name | Credits (cr) |
|---|---|---|
|
CORE COMPETENCE
(Choose all) |
40 | |
| YDATTS24-1001 |
Planning for the Future
(Choose all) |
10 |
| MS00BP40 | Future Operating Environments | 5 |
| MS00BP16 | Research and Development Methods | 5 |
| YDATTS24-1002 |
Basics of Data Engineering & AI
(Choose all) |
10 |
| MS00CN43 | Introduction to Data Engineering and AI Technologies | 5 |
| MS00CN44 | Introduction to Cloud Technologies and Security | 5 |
| YDATTS24-1003 |
Data Engineering
(Choose all) |
10 |
| MS00CN45 | MLOps | 5 |
| MS00CN46 | Data Engineering project | 5 |
| YDATTS24-1004 |
Artificial Intelligence
(Choose all) |
10 |
| MS00CN47 | Components and Application of Artificial Intelligence | 5 |
| MS00CN48 | AI project | 5 |
|
COMPLEMENTARY COMPETENCE
(Choose 20) |
20 | |
| YDATTS24-1005 |
Optional Studies
(Choose ects: 20) |
20 |
|
MASTER'S THESIS
(Choose all) |
30 | |
| MS00BP41 | Master's Thesis | 30 |