Data Science

Data scientist, AI expert, data engineer, data analyst – the Master’s programme in Data Science at the University of Regensburg prepares you for all of these roles. You will also be qualified to work in a wide range of application domains, including biomedical research, the technology sector, business, and other future‑oriented fields. The MSc in Data Science equips you to develop innovative solutions to complex problems and to work confidently in interdisciplinary environments. During your studies, you will deepen your knowledge in advanced topics of statistics and machine learning and specialise in selected areas of application. The programme is structured into three components: Compulsory area (including Master’s thesis) – minimum 66 ECTS Compulsory elective area “Machine Learning and Statistics” – minimum 12 ECTS Compulsory elective area “Specialisation” – minimum 42 ECTS Compulsory Area: Building a Strong Foundation A solid understanding of current developments in deep learning and reinforcement learning is essential in modern data science. You will acquire this knowledge at the beginning of your studies in the module Modern Machine Learning with an accompanying lab (6 ECTS). Two Free Elective modules allow you to choose courses from computer science, data science, or other disciplines according to your interests (12 ECTS each). The compulsory area also includes a seminar on current topics in data science (6 ECTS) and the Master’s thesis (30 ECTS). Machine Learning and Statistics: The Core of the Programme In this compulsory elective area, you select modules worth at least 12 ECTS from a catalogue of 11 advanced courses covering central topics in data science and machine learning. Examples include Statistical Machine Learning, Advanced Statistics I and II, Advanced Explainable AI, Advanced Data Engineering, and Digital Image Processing – AI‑based Approaches. Specialisation Area: Tailoring Your Profile You choose one of four specialisations and complete at least 42 ECTS within that track (according to defined regulations). The available specialisations are: Machine Learning and Statistics Computational Life Sciences Human‑Centred Data Science Information Systems Each specialisation includes its own compulsory elective structure, allowing you to select modules that match your academic interests. Choosing one specialisation is mandatory. If you write your Master’s thesis on a topic from that specialisation, the specialisation will be listed on your Master’s certificate. Our Courses You will take part in lectures with accompanying labs, seminars, project seminars, and "practicums". In lecture‑lab formats, you acquire theoretical knowledge in the lecture and apply it independently in the lab sessions. Labs usually include exercises as coursework, which may be mandatory or optional. Examinations typically consist of written or oral exams that assess both conceptual understanding and methodological skills. Seminars enable you to explore a scientific topic in data science independently, understand the current state of research, and prepare and present scientific work. Coursework usually includes a presentation, while the examination consists of a written paper. Across all specialisations, project seminars and practicums offer hands‑on research experience. Students—often working in teams—conduct an independent research project as preparation for the Master’s thesis. Coursework includes a project presentation, and the examination usually consists of a project report or documentation. PDF Download