Denmark

Data Science entry scores in Denmark (2026): cut-off marks by university

We have official entry scores for 6 programmes (scale from 2 to 12, higher is better). In the latest lists the score of the last admitted student ranged from 5.9 to 11.2. The most selective programme was at Aarhus University (Aarhus), the most accessible at IT University of Copenhagen.

Always check current information on the official website of the university before you apply.

ProgrammeUniversityCity202620252024
Data ScienceAarhus University (Aarhus)Aarhus11.210.1—
Kognitions- og datavidenskabUniversity of Copenhagen (København)Copenhagen10.510.910.6
Teknisk videnskab (Civilingeniør) Data science og managementTechnical University of Denmark (Kongens Lyngby)Kongens Lyngby8.39.39.8
Machine learning og datavidenskabUniversity of Copenhagen (København)Copenhagen——6
DatavidenskabAarhus University (Aarhus)Aarhus66.1—
Data ScienceIT University of CopenhagenCopenhagen5.938.4

The score is the result of the last admitted student, so it changes every year.

How admission works in Denmark

You apply through Optagelse.dk, the national portal of the Coordinated Admission (KOT): you can list up to 8 programmes and receive at most one offer, at your highest possible priority. You need a qualification on a level with the Danish upper secondary leaving certificate plus each programme's specific requirements, and Danish-taught programmes require proof of Danish. Where there are more applicants than places, quota 1 selects by grade point average (the score shown is the quota 1 cut-off on the Danish 7-point scale) and quota 2 by criteria set by the institution. For the 2027 intake Optagelse.dk opens on 1 February 2027; the deadline is 15 March 2027 at 12:00 for quota 2 and for anyone with a foreign or international (IB) diploma, and 5 July 2027 at 12:00 for quota 1 with a Danish diploma; answers come on 28 July.

See also: All Data Science programmes in Denmark · Entry scores in Denmark · Study in Denmark

Sources

How the figures are collected and calculated: Data and sources.