The master’s programme in Data Science takes two years to complete, and each academic year is divided into two semesters.
The first 3 semesters consist of fundamental courses, profile courses, and an elective module. In the fourth semester, you work on your Master’s thesis project.
The course of study depends on which of the following profiles you choose.
This profile qualifies you to carry out data processing and make informed decisions on the basis of large amounts of data, as well as to understand the use of modern technology and innovation as a competitive parametre in manufacturing companies and companies within the service sector.
The profile is tailored towards students with a Bachelor’s degree in economics, business administration or the like.
The diagramme below gives you an overview of the course of study. 
On small screen it works best in landscape mode.
This profile qualifies you to work with technology on a value-based and people-oriented basis. Moral and ethical choices must be made every day, and value can be created through linguistic and image-based data.
The profile is tailored towards students with a Bachelor’s degree within the humanities, business or social sciences.
The diagramme below gives you an overview of the course of study. On small screens it works best in landscape mode.
This profile gives you general competences within information and communication technologies.
You will gain a deeper knowledge of information and communication technology systems, including computer networks and cloud computing, programming, a broad introduction to algorithms and data structures, as well as network and cyber security.
The diagramme below gives you an overview of the course of study. On small screens it works best in landscape mode.
Below is an example of what a schedule might look like for a student in the first semester of the master’s programme in Data Science. Class times and workload may vary from week to week, and as a rule, classes can be scheduled on weekdays between 8:15 AM and 6:00 PM.
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
|---|---|---|---|---|
9:15-11:00 AMFind literature for assignment |
8:15 AM-12:00 PMRead literature and take notes |
8:15-10:00 AMLecture[Statistics] |
8:15-10:00 AMRead literature and take notes |
|
10:15 AM-12:00 PMSkim articles and take notes before lecture |
10:15 AM-12:00 PMGroup instruction[Statistics] |
10:15 AM-12:00 PMGroup instruction[Linear Algebra] |
||
12:15-2:00 PMWork on assignment with study group |
12:15-2:00 PMLecture[Linear Algebra] |
12:30-2:00 PMRead literature on campus |
||
2:15-4:00 PMLecture[Linear Algebra] |
2:15-5:00 PMGroup instruction[specialisation course] |
2:15-4:00 PMPrepare oral presentation |
2:15-4:00 PMGroup discussion on the week’s teaching |
2:15-4:00 PMLecture[Programming] |
5:15-8:00 PMWork on written assignment |
4:15-6:00 PMGroup instruction[Programming] |