Education Programs at LMU and TU Munich

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Current Courses

Our programs are taught by experienced researchers and educators, who are experts in their respective fields and provide students with the opportunity to learn from and collaborate with them.

We offer a wide range of courses covering various aspects of AI and ML, such as deep learning, reinforcement learning, natural language processing, computer vision, and much more. If you are looking to gain a deeper understanding of AI and ML, we have a program that is right for you.

Here you will find links to courses related to Artificial Intelligence and Machine Learning in the current semester at the Munich Center for Machine Learning, LMU Munich, and TU Munich. The list does not claim to be complete, if you offer a course that you would like to have included here, please contact us at contact@mcml.ai.

Lectures, Seminars and Practicals at LMU Munich

• Prof. Dr. Bernd Bischl: Statistical Learning and Data Science
• Prof. Dr. Anne-Laure Boulesteix: Biometry in Molecular Medicine
• Prof. Dr. Stefan Feuerriegel: Artificial Intelligence (AI) in Management
• Prof. Dr. Eyke Hüllermeier: Artificial Intelligence and Machine Learning
• Prof. Dr. Michael Ingrisch: Clinical Data Science in Radiology
• Prof. Dr. Göran Kauermann: Applied Statistics in Social Sciences, Economics and Business
• Prof. Dr. Frauke Kreuter: Statistics and Data Science in Social Sciences and the Humanities (SODA)
• Prof. Dr. Helmut Küchenhoff: Statistical Consulting Laboratory (StabLab)
• Prof. Dr. Gitta Kutyniok: Mathematical Foundations of Artificial Intelligence
• Prof. Dr. Christian Müller: Biomedical Statistics and Data Science
• Prof. Dr. Sven Nyholm: Ethics of Artificial Intelligence
• Prof. Dr. Björn Ommer: Computer Vision & Learning Group
• Prof. Dr. Holger Rauhut: Mathematical Data Science and Artificial Intelligence
• Prof. Dr. David Rügamer: Data Science Group
• PD Dr. Fabian Scheipl: Functional Data Analysis
• Prof. Dr. Volker Schmid: Bioimaging
• Prof. Dr. Albrecht Schmidt: Human-Centered Ubiquitous Media
• Prof. Dr. Matthias Schubert: Database Systems and Data Mining
• Prof. Dr. Thomas Seidl: Database Systems and Data Mining
• Prof. Dr. Volker Tresp: Database Systems and Data Mining
• Prof. Dr. Ralf Zimmer: Bioinformatics

Lectures, Seminars and Practicals at TU Munich

• Prof. Dr. Zeynep Akata: Interpretable and Reliable Machine Learning
• Prof. Dr. Matthias Althoff: Cyber Physical Systems
• Prof. Dr. Ulrich Bauer: Applied and Computational Topology
• Prof. Dr. Alena Buyx: Ethics in Medicine and Health Technologies
• Prof. Dr. Daniel Cremers: Computer Vision and Artificial Intelligence
• Prof. Dr. Angela Dai: 3D AI Lab
• Prof. Dr. Mathias Drton: Mathematical Statistics
• Prof. Dr. Massimo Fornasier: Applied Numerical Analysis
• Prof. Dr. Alexander Fraser: Data Analytics & Statistics
• Prof. Dr. Julien Gagneur: Computational Molecular Medicine
• Prof. Dr. Stephan Günnemann: Data Analytics and Machine Learning
• Prof. Dr. Reinhard Heckel: Machine Learning
• Prof. Dr. Niki Kilbertus: Ethics in Systems Design and Machine Learning
• Prof. Dr. Felix Krahmer: Optimization and Data Analysis
• Prof. Dr. Stefan Leutenegger: Machine Learning for Robotics
• Prof. Dr. Nassir Navab: Computer Aided Medical Procedures & Augmented Reality
• Prof. Dr. Matthias Nießner: Visual Computing
• Prof. Dr. Daniel Rückert: Artificial Intelligence in Healthcare and Medicine
• Prof. Dr. Julia Schnabel: Computational Imaging and AI in Medicine
• Prof. Dr. Angela Schöllig: Safety, Performance and Reliability of Learning Systems
• Prof. Dr. Björn Schuller: Health Informatics
• Prof. Dr. Suvrit Sra: Resource Aware Machine Learning
• Prof. Dr. Fabian Theis: Mathematical Modelling of Biological Systems
• Prof. Dr. Nils Thuerey: Physics-based Simulation)
• Prof. Dr. Christian Wachinger: Artificial Intelligence in Radiology
• Prof. Dr. Rüdiger Westermann: Computer Graphics and Visualization
• Prof. Dr. Xiaoxiang Zhu: Data Science in Earth Observation