Master of Engineering, Data Engineering and AI: DATIS ajoitus
Code: YDATIS23
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.
Select timing, structure or classification view
Show study timings by semester, study year or period
| Code | Name | Credits (cr) | 2023-2024 | 2024-2025 | Autumn 2023 | Spring 2024 | Autumn 2024 | 1. / 2023 | 2. / 2023 | 3. / 2024 | 4. / 2024 | 5. / 2024 | 1. / 2024 | 2. / 2024 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
CORE COMPETENCE
(Choose all) |
20 | |||||||||||||
| YDATIS23-1002 |
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 | ||||||||
| YDATIS23-1004 |
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 | ||||||||
|
COMPLEMENTARY COMPETENCE
(Choose 10) |
10 | |||||||||||||
| YDATIS23-1003 |
Optional Studies
(Choose ects: 10) |
10 | 10 | 10 | 3.3 | 3.3 | 3.3 | |||||||
| YDATIS23-1005 |
Data Engineering
(Choose 10) |
0 - 10 | ||||||||||||
| MS00CN45 | MLOps | 5 | ||||||||||||
| MS00CN46 | Data Engineering project | 5 | ||||||||||||
| YDATIS23-1006 |
Artificial Intelligence
(Choose 10) |
0 - 10 | ||||||||||||
| MS00CN47 | Components and Application of Artificial Intelligence | 5 | ||||||||||||
| MS00CN48 | AI project | 5 | ||||||||||||
|
MASTER'S THESIS
(Choose all) |
30 | |||||||||||||
| MS00BP41 | Master's Thesis | 30 | 10 | 20 | 10 | 20 | 3.3 | 3.3 | 3.3 | 10 | 10 | |||
| Total | 60 | 30 | 20 | 20 | 10 | 20 | 10 | 10 | 3.33 | 3.33 | 3.33 | 10 | 10 |
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) |
20 | |
| YDATIS23-1002 |
Planning for the Future
(Choose all) |
10 |
| MS00BP40 | Future Operating Environments | 5 |
| MS00BP16 | Research and Development Methods | 5 |
| YDATIS23-1004 |
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 |
|
COMPLEMENTARY COMPETENCE
(Choose 10) |
10 | |
| YDATIS23-1003 |
Optional Studies
(Choose ects: 10) |
10 |
| YDATIS23-1005 |
Data Engineering
(Choose 10) |
0 - 10 |
| MS00CN45 | MLOps | 5 |
| MS00CN46 | Data Engineering project | 5 |
| YDATIS23-1006 |
Artificial Intelligence
(Choose 10) |
0 - 10 |
| MS00CN47 | Components and Application of Artificial Intelligence | 5 |
| MS00CN48 | AI project | 5 |
|
MASTER'S THESIS
(Choose all) |
30 | |
| MS00BP41 | Master's Thesis | 30 |