Structure of the Master Specialisation Data Science
The list below illustrates the basic organization of the 120 EC Data science master specialisation,[1] which consists of the following components:
- Specialisation basis (18 EC)
- Specialisation electives (24 EC)
- Specialisation specific research seminar (6 EC)
- Computer science and Society (philosophy course) (3 EC)
- Research internship (15 EC)
- Master electives (18 EC)
- Free electives (6 EC)
- Master thesis project (30 EC)
The total amount of EC's of this programme should be at least 120 EC.
The components are further refined as follows:
Specialisation basis (mandatory courses) (18 EC): |
Specialisation electives (24 EC): Data Science Theory and Tools
Data Science Applications
Data Science Aspects |
Specialisation specific research seminar (6 EC) |
Computer science and Society (philosophy course) (3 EC) |
Research internship (15 EC) |
Master electives (18 EC) |
Free electives (6 EC) |
Final thesis (30 EC): MSc-project. |
_______________________________________________________________________________
[1] The programme described here is the research specialisation Data Science. Students who are more interested in taking a more applied and/or management related angle may have a look at the societal specialisations Science, Management and Innovation or Science in Society, which can also be taken with a Data Science programme (see the master-specific requirements for Computing Science at the bottom of these respective pages).
[2] The Examination Board can also approve the inclusion a maximum of 6 EC of Bachelor’s courses in the elective space, provided that (a) the course was not taken by the student as part of their bachelor or pre-master programme; (b) the student is able to motivate this choice, and (c) the Bachelor’s courses have a thematic coherency with the other courses in the elective space.