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Curriculum Computational Engineering

The core curriculum comprises the required courses of the Master's program.  The accompanying elective courses can be choosen from the pool of Master's courses.  For details consult the Curriculum Guide.

Core Course Catalog

Winter Semester
Machine Learning: Supervised Techniques 2 VO + 1 UE Hochreiter
Model Checking 3 KV Biere
Probabilistic Models 2 VO + 1 UE* Widmer
System Software 2 KV Mössenböck
Summer Semester
Computer Algebra for Concrete Mathematics 2 VO + 1 UE* Paule
Hardware Design 2 VO + 1 UE Ostermann
Parallel Computing 3 KV Strumpen

* 1 UE is a recommended elective


JKU offers a pool of about 50 Master's courses to complement the core curriculum. Below, you find three samples of possible choices if your technical preferences lean towards AI, Systems, or Theory. However, you are free to choose and tailor the electives according to your personal interest.

Artificial Intelligence
Basic Methods of Data Analysis 2 KV Hochreiter
Machine Learning and Pattern Classification 3 KV Widmer
Machine Learning: Unsupervised Techniques 2 VO + 1 UE Hochreiter
Theoretical Concepts of Machine Learning 2 VO + 1 UE Bodenhofer
Visual Analytics 2 VO Streit
Advanced Compiler Construction 2 KV Mössenböck
Computer Architecture 2 3 KV Strumpen
Computer Vision 3 KV Bimber
Debugging 2 KV Biere
Principles of Programming Languages 2 KV Blaschek/Prähofer
VLSI Design 2 KV Ostermann
Advanced Model Checking 2 KV Biere
Computer Algebra 2 VO + 1 UE Winkler
Computational Geometry 2 VO + 1 UE Jüttler
Formal Methods in Software Development 3 KV Schreiner
Formal Semantics of Programming Languages 2 VO Schreiner
Rewriting in Computer Science and Logic 2 VO Kutsia
Special Topics
Colloquium Computational Engineering 2 SE Strumpen