Skip to main content
DA / EN

Structure of the programme

The Master’s Degree 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, specializing 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 areas of specialization you choose.

This area of specialization 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 mobile devices it works best in landscape mode.

This area of specialization 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 mobile devices it works best in landscape mode.

This area of specialization 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 mobile devices it works best in landscape mode.

Example of schedule

Below is an example of how your weekly schedule might look like in the first semester of the Master’s programme in Data Science at SDU Kolding. Please note that your schedule may vary from week to week and that teaching activities may be scheduled on weekdays in the hours between 8.15 and 18.30.

Monday
Tuesday
Wednesday
Thursday
Friday

9-12
Statistics (lecture)
9-11
Linear algebra (lecture)
9-12
Statistics (lecture) 

11-13.30
Programming (lecture)

11-13.30
Programming (lecture)

 

10-14.30
Specialization course
13.45-15.30
Programming (practice session) 
 
13.45-15.30
Linear algebra (practice session)

15.45-17.30
Statistics (practice session)
16.45-18.30
Statistics (practice session)