About this programme
The consecutive Master's degree programme in Artificial Intelligence at the University of Bonn, a collaboration with the Lamarr Institute for Machine Learning and Artificial Intelligence, is strongly application- and research-oriented, focusing on the mathematical foundations, training, and deployment of advanced AI models to solve complex, real-world problems. A close connection between the specialised courses on offer and the cutting-edge research carried out by our various working groups shapes this degree programme, which is why it is particularly suitable for driven students seeking to deepen their knowledge and develop their technical skills. We also work closely with internationally renowned research institutions and technology companies in and around Bonn. This gives our students the opportunity to work on state-of-the-art AI projects and gives them a wide range of exciting, highly relevant topics for their research and graduation projects – a rapid launchpad into an advanced tech role or a scientific career. Through interdisciplinary work and projects anchored in the programme, students acquire key interdisciplinary skills, including the assessment of problems in AI ethics and societal implications. The degree is awarded to students for finishing the minimum required course work (and their final Master's thesis) in five categories: foundations, specialisation, advanced, interdisciplinary modules, and ethical, legal, and social aspects. You can choose freely from the modules available each semester, provided you pass: two compulsory modules in foundations at least 12 ECTS in specialisation at least 39 ECTS in advanced (including one lab and one seminar) at least 10 ECTS in interdisciplinary modules at least 4 ECTS in ethical, legal, and social aspects The Master's thesis and its presentation amount to 32 ECTS. Coursework includes lectures with exercises (6-9 ECTS), labs (9-10 ECTS) and seminars (4 or 6 ECTS). A full semester comprises 30 ECTS. In foundations (first semester), students are required to attend two lectures that provide the basis of modern machine learning approaches. Principles of Machine Learning (6 ECTS) Principles of Deep Learning (6 ECTS) In specialisation (first and second semester), students attend two or three courses to gain a knowledge base for a specialised direction, such as: Audio and signal processing Computer vision Computer graphics and image analysis Geometry processing and numerics Neuroscience and medicine Robot learning Natural language processing Data science In advanced (second and third semesters), students perform advanced domain-specific coursework in different specialised areas. This includes a seminar and research-focused lab work in an application domain, for example: explainable AI, alignment, and ethics virtual environments data science and data mining AI in graphics, vision, and audio embodied and agentic AI AI in biomedical sciences Self-supervised and reinforcement learning In interdisciplinary projects (third semester), students work on an interdisciplinary project of their choosing, a collaborative research project in an adjacent field and a hallmark of the degree. Here, AI is applied to a real-world problem. Possible areas currently include: ethics geodesy life and medical sciences physics neuroscience crop production Ethical, social and legal aspects implies course work in ethical, social, or legal aspects relating to AI.
Course details verified 10 Sep 2026 — intakes, entry requirements and course facts · official source