Master's Programme in Computer Science

Learning outcomes

Upon completion of the Master's degree the student
- masters at least one sub-field in computer sciences in depth
- knows scientific thinking and can apply scientific working methods in his or her own field of specialization
- is motivated for life-long learning
- has the required skills and knowledge for post-graduate studies
- can apply newly acquired information and operate in international working situations
- can communicate in professional and scientific contexts
- knows the ethical norms in his or her specialization and can apply them in his or her work.

Studies in the Master's programme in Computer Science are divided into specializations. In addition to the general goals of the Master's programme, each specialization has its own goals. Below you can find the learning outcomes of each specialization


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Master's Programme in Computer Science

Advanced Studies in Master's Programme in Computer Science 80 ECTS
Advanced Studies in Computer Science 40– ECTS
TIETS02 Automata I, 5 ECTS
TIETS03 Automata II, 5 ECTS
TIETS26 Conceptual Modelling I, 5–10 ECTS
TIETS27 Conceptual Modelling II, 5–10 ECTS
TIETS21 Master's Thesis Seminar, 5 ECTS
TIETS17 Requirements Engineering, 5 ECTS
TIETS12 Computer Graphics, 10 ECTS
TIETS36 Research project, 1–10 ECTS
TIETS01 Algorithms, 5 ECTS
TIETS11 Data Mining, 5 ECTS
TIETS05 Digital Image Processing, 5 ECTS
TIETS31 Knowledge Discovery, 5–10 ECTS
TIETS07 Neurocomputing, 5 ECTS
TIETS43 Recommender Systems, 5 ECTS
ITIS14 Web Science, 5 ECTS
Advanced Studies in CS, Computational Methods
TIETS01 Algorithms, 5 ECTS
TIETS02 Automata I, 5 ECTS
TIETS03 Automata II, 5 ECTS
TIETS21 Master's Thesis Seminar, 5 ECTS
TIETS07 Neurocomputing, 5 ECTS
TIETS11 Data Mining, 5 ECTS
TIETS05 Digital Image Processing, 5 ECTS
TIETS31 Knowledge Discovery, 5–10 ECTS
TIETS12 Computer Graphics, 10 ECTS
TIETS43 Recommender Systems, 5 ECTS
Master's thesis 40 ECTS
TIETS37 M.Sc. Thesis, 40 ECTS
Faculty of Natural Sciences