Computer Science

This English-taught master's builds on a broad foundation in computer science while giving you freedom to deepen either core theoretical and technical topics or application-oriented areas. The programme balances compulsory modules (including an advanced seminar and a substantial master’s thesis) with two elective streams: a Core Computer Science elective area and a Specialisation elective area. Teaching combines lectures, labs and seminars, and the curriculum emphasises advanced software engineering and algorithmic skills as central competencies.

In the Core Computer Science elective area you pick from a wide catalogue of scheduled modules covering theoretical CS, computer engineering, practical programming and applied topics. This lets you tailor your studies toward fields like machine learning, cryptography, embedded systems, data engineering or AI-based image processing. If you choose to take a tracked specialisation, you can further concentrate your studies in one of four defined pathways; completing your master’s thesis within that specialisation will have the specialisation noted on your degree certificate.

This structure makes the programme flexible for students aiming for research or industry careers. International students should expect a mix of coursework and hands-on labs, close supervision for the thesis project, and opportunities to collaborate with research groups or partners in applied domains. Practical experience with software development and strong mathematical foundations will help you succeed in the advanced modules.

Requirements and structure (concise)

• Programme language: English.
• Three main parts:
  • Compulsory area (minimum 60 ECTS), includes:
    • Two required lectures with associated labs: Advanced Software Engineering and Advanced Algorithms (6 ECTS each).
    • An elective module in computer and data science (12 ECTS).
    • Seminar on current topics in computer science (6 ECTS).
    • Master’s thesis module (30 ECTS).
  • Compulsory elective area "Core Computer Science" (at least 18 ECTS):
    • Choose three modules (≥18 ECTS) from about 20 offerings across theoretical CS, computer engineering, practical CS and applied CS.
    • Sample modules: Topics in Theoretical Computer Science; Modern Machine Learning; Advanced Explainable AI; Embedded Systems; Advanced Data Engineering; Digital Image Processing – AI-based Approaches; Post-Quantum Cryptography.
  • Compulsory elective area "Specialisation" (at least 42 ECTS if you opt for a full specialisation):
    • Four available specialisations: Core Computer Science, Bioinformatics, Human-Centred Computing, Information Systems.
    • Each specialisation includes its own compulsory-elective rules so you can tailor module choices.
    • If you complete your master’s thesis as part of a chosen specialisation, that specialisation will be indicated on your Master’s certificate.
• Note on specialisation: the programme allows you to specialise by completing ≥42 ECTS in one track; the programme also requires that you select a specialisation pathway (see programme regulations for details).

Program structure and goals

This MSc programme develops advanced expertise across core and applied areas of computer science while allowing you to specialise in application domains of your choice. The degree requires 120 ECTS in total and combines mandatory core modules, a selectable core-computer-science pool, and a larger specialisation component, culminating in a research-focused Master’s thesis. Key compulsory modules named in the curriculum include Advanced Algorithms, Advanced Software Engineering, Current Topics in Computer Science and a Free Elective, alongside the Master’s thesis.

Teaching formats and learning outcomes

Teaching is delivered through lectures with accompanying labs, seminars, and project seminars or practicums (including internships). Labs convert lecture concepts into hands‑on exercises and coursework so you learn to apply methods independently. Seminars train you to research current scientific questions, prepare and critique presentations and written papers, and deepen subject-matter literacy. Project seminars and practicums emphasise team-based applied research: you plan and present a project and submit a project paper or documentation, providing direct preparation for the Master’s thesis. Typical assessments include written or oral exams, coursework, presentations and project reports.

Timeline and specialisation

Coursework from the compulsory area, the Core Computer Science elective pool, and your chosen Specialisation is taken mainly during the first three semesters. The fourth semester is reserved for completing the Master’s thesis and its associated deliverables. Further specifics about available specialisation modules and detailed course descriptions are provided in the programme’s overview/description materials.

Requirements (concise)

• Total credits: 120 ECTS required for the Master’s degree.
• Compulsory area: at least 60 ECTS (includes Advanced Algorithms; Advanced Software Engineering; Free Elective; Current Topics in Computer Science; and the Master’s thesis).
• Compulsory elective — “Core Computer Science”: at least 18 ECTS. A total of 20 modules (each 6 ECTS) are offered in this pool: 9 modules from theoretical computer science, 3 from computer engineering, and 8 from practical & applied computer science.
• Compulsory elective — “Specialisation”: at least 42 ECTS (see programme overview for detailed module lists and specialisation tracks).
• Study rhythm: courses from all areas are taken during semesters 1–3; semester 4 is dedicated to the Master’s thesis.
• Assessment methods: written/oral exams, lab coursework, seminar presentations and papers, project documentation and presentations.

Graduates are prepared for a broad range of technical and research roles in industry and academia. The programme’s emphasis on advanced algorithms, software engineering, data engineering, machine learning, cryptography, image processing and embedded systems qualifies graduates for positions such as software engineer, data scientist/machine learning engineer, systems or embedded engineer, security/cryptography specialist, bioinformatics analyst, and HCI specialist in sectors including IT companies, medtech, automotive, finance, research institutes and startups.

The research- and project-oriented structure (project seminars and a 30 ECTS Master’s thesis) also provides a direct pathway to R&D roles or further academic work (PhD). The flexible elective and specialisation choices enable tailoring skills to specific industry needs or research topics, improving employability in both applied and theoretical computing fields.