Programme Structure

The part-time MSc in Computer Science is a four-year programme concluding with a master's thesis.

You can select from and combine a wide range of courses during your studies, such as: digital imaging, programming languages, distributed and parallel systems, systems engineering, human-machine interfaces, combinatorial optimization, and computer games.

Study Tracks

You have the chance to study a subject area in depth. By selecting different elective and restricted elective courses you can either compose a programme of your own or choose one of seven available study tracks.

Read more about study tracks >>

Do a Project in Practice

You can use some of your elective courses to do a Project in Practice in collaboration with a company or an organization.

Master's Thesis

Your degree is capped off with the thesis. Below is a list of previous thesis topics to give you an idea of what is possible:

• Counting Problems in Massive Graphs
• Enforcing Data Consistency in Event-Driven Microservices through Event-Based Constraints
• Generative Neural Networks for Ecosystem Simulation
• Identifying and Utilizing Reliable Agents in Real-Time Crowdsourcing Tasks
• Plant Health and Food Quality Qith RGB and Deep Learning
• Predictive Protein Stability Modeling Through Gaussian Processes and Encoding Methods
• Parallel Implementations of Machine Learning Algorithms
• Security Issues in eBPF Verifier
• Using Deep Learning for Image Segmentation of MRI Scans
• Generative Neural Networks for Ecosystem Simulation
• Implementation of a Blockchain with Native DCR Graphs Smart-Contracts
• Cooperative Virtual Reality Environment for Training Teamwork in the Maritime Business
• Game Physics Engine for Interactive Fluid Effects

Programme Overview

Compulsory courses: 22.5 ECTS
Restricted elective courses: 37.5 ECTS
Elective courses: 30 ECTS
Master's thesis: 30 ECTS

One block comprises nine weeks of study + relevant employment, and equals 7.5 ECTS.

Restricted Elective Courses

Choose your restricted elective courses from the lists below. Click on each course for a detailed description.

You must choose at least one course from the following list:

• Advanced Topics in Deep Learning
• Advanced Topics in Machine Learning
• Deep Learning
• Machine Learning A
• Machine Learning B
• Natural Language Processing

Choose your remaining courses from this list:

• Advanced Topics in Deep Learning
• Advanced Topics in Human-Centered Computing
• Approximation Algorithms
• Computability and Complexity
• Computational Geometry
• Computational Methods in Simulation
• Computer Game Development Project (30 ECTS)
• Deep Learning
• IT Innovation and Change
• Medical Image Analysis
• Mobile Computing
• Neural Information Retrieval
• Numerical Optimization
• Online and Reinforcement Learning
• Proactive Computer Security
• Program Analysis and Transformation
• Programming Massively Parallel Hardware
• Randomized Algorithms
• Semantics and Types
• Signal and Image Processing
• Software Engineering and Architecture (15 ECTS)
• User Interface Technology
• Visualisation
• Project outside the course scope (7.5 or 15 ECTS)
• Thesis preparation project