Depending on the prior knowledge of the student, the student follows one the following Pre-Master programs of 30 ECTS (6 courses):
Pre-master program for students with prior knowledge in linear algebra
| Quarter | Code | Unit | Timeslot | ECTS |
1 | 2IHA10 | Algorithms and Data Structures | A | 5 |
1 | 2IT60 | Logic and Set theory | D | 5 |
1 | 2DI90 | Probability & Statistics | C | 5 |
2 | 2IIG0 | Data Mining and Machine Learning | C | 5 |
2 or 3 | 2ID50 | Data modeling and databases Data Management for Data Analytics | E or B | 5 |
2 | JBI100 | Visualization |
Pre-master program for students with prior knowledge in probability and statistics
| Quarter | Code | Unit | Timeslot | ECTS |
1 | 2WF20 | Linear Algebra 1 | A | 5 |
1 | 2IT60 | Logic and Set theory | D | 5 |
2 | 2IIG0 | Data Mining/Machine Learning | C | 5 |
2 or 3 | 2ID50 | Data modeling and databases Data Management for Data Analytics | E | 5 |
2 | JBI100 | Visualization | D | 5 |
3 | 2IL50 | Data Structures |
Pre-master program for students with further prior knowledge
Students who satisfy further prior knowledge requirements for DS&AI can follow a reduced pre-Master program. Students with a university-level Bachelor degree who have a deficit of at most 15 ECTS (3 courses) can be admitted to DS&AI with the missing courses as homologation courses to follow during the Master program.