This English‑taught Master's programme is a 90 credit‑point course of study designed to advance graduates of Bachelor's programmes into a scientific Master's degree. The curriculum builds on prior undergraduate training and prepares students to take on more advanced, research‑oriented work in computer science.
The programme is especially attractive for students who want to broaden or deepen their expertise in media technologies and artificial intelligence. It is well suited to holders of international Bachelor's degrees in computer science and related technical disciplines who are looking for an English‑language pathway to further study in Germany.
For more details and frequently asked questions, see: https://www.haw-kiel.de/en/degree-courses/courses/computer-science
Curriculum overview
This master's curriculum is structured over three semesters and mixes advanced taught modules with a substantial research orientation. In the first semester you take core technical courses—Advanced Application Programming, Advanced Cloud Computing, Advanced Software Engineering, and Distributed Databases and Information Systems—alongside a set of compulsory elective modules. Elective examples offered in the program include Deep Learning (Artificial Intelligence track) and Ubiquitous Computing & Media (Computer Science for Media track); you also choose an additional elective to round out your first-semester workload. These courses build a foundation in modern software and distributed systems design, cloud-native architectures, and scalable data management.
The second semester emphasizes independent research and specialization. You undertake a Computer Science research project and continue with compulsory elective modules such as Pattern Recognition (AI track) or Audio/Video Design and Interaction (Media track), plus two further elective modules. This semester is designed to deepen your technical expertise in a focused area, prepare you to apply research methods, and give practical experience in designing and evaluating systems or models.
In the third semester you produce your master’s thesis and participate in a colloquium to present and defend your work. The program offers an optional study focus so you can formally specialise in either Artificial Intelligence or Computer Science for Media. Overall learning outcomes include advanced programming proficiency, the ability to design and deploy cloud and distributed systems, competency in modern software engineering practices, applied knowledge of AI methods (such as deep learning and pattern recognition) or multimedia computing, and the capacity to carry out and communicate independent research—skills relevant for industry roles and further academic study.
Program requirements (concise)
Applicants must meet both academic and standardized-test requirements. You need a relevant three- or four-year university degree (for example: Bachelor’s in information technology, computer science, business informatics, or an equivalent qualification in a related subject) from a recognised institution, and your final grade must be at least 2.5 when expressed on the German grading scale. This grade requirement is applied strictly; exceptions are not possible.
In addition, you must demonstrate sufficient quantitative aptitude on the GRE: a minimum of the 55th percentile in the Quantitative Reasoning section is required. The GRE result must be verifiable (official score report) — no exceptions. Make sure your transcripts clearly indicate the grading scale used or provide an official conversion to the German system if available, and confirm that your degree is recognised by the university’s admission office before applying.
Admission requirements (summary)
Winter Semester (International)
15 September 2026
Summer Semester (International)
15 March 2026
Winter Semester (EU/EEA)
15 September 2026
Summer Semester (EU/EEA)
15 March 2026
Graduates are prepared for technical and research-oriented roles in software engineering, AI and machine learning, data science, multimedia computing, and related fields. The programme's applied focus and specialised modules (e.g., deep learning, pattern recognition, cloud computing, distributed databases) equip students for industry positions in technology companies, startups, and media firms. The Master also provides a scientific foundation for continuing to doctoral studies (PhD) or taking on R&D roles. Practical project work and international collaborations enhance employability in both German and international job markets.
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