Study Type

graduate

Admission semester

Summer and Winter Semester

Focus

Algorithms and Data Engineering, Machine Learning, Mathematical Methods, Process Mining, Deep Learning, Computer Vision, Quantum Algorithms, Natural Language Understanding, Mathematical Modelling; Statistics, High-Dimensional Probability; Ethics and Computer Science

Target group

The degree course is aimed at students with a BSc degree in Data Science, Computer Science, Mathematics or related fields.

Admission modus

Selection procedure / qualifying examination

More information regarding admission requirements

Admission requirements

Admission is based on an aptitude procedure, which is laid down in Section 4 and Annex I of the examination regulations. This requires, among other things, an average grade of 2.70 or better in the previous BSc degree programme. Furthermore, proof of the following knowledge from the Bachelor’s degree is expected: - Multidimensional Analysis (at least 5 CP ECTS) - Abstract Structures of (Linear) Algebra (at least 5 CP ECTS) - Basics of an Advanced Programming Language (at least 4 CP ECTS) - Practical Programming (at least 4 CP ECTS) - Algorithms or Numerical Procedures (at least 5 CP ECTS) - Discrete Structures, Databases or Data Engineering (at least 5 CP ECTS) -Data Science or Machine Learning (at least 4 CP ECTS)

Tuition fees

More information regarding tuition fees