We do NOT list courses on this website which have an additional registration phase, like the seminars and some of the programming courses. Information on the registration for such courses will be distributed by our deans office via round-mail.

This list is not intended to be exhaustive or accurate; in case of doubt, the information provided in the course catalog and by the instructors themselves shall prevail.

Department of Statistics

• Advanced Statistical Learning, Prof. Groll, MD1, 9 ECTS, Tue, 16-18; Thu, 16-18
• Causality, Prof. Marx, MD E1, 4.5 ECTS, Thu, 14-16; Fri, 12-14
• Generalized Linear Models, Prof. Groll, MD E1, 9 ECTS, (Tue, 10-12), Wed, 12-14
• Hidden Markov and State Space Models, Dr. Michels, MD E1, 4.5 ECTS,Thu, 10-12
• Statistical Methods for Counting Processes Dr. Jakubzik, MD E1, 9 ECTS Mon, 12-14; Tue, 10-12
• Industrial Data Science II, Prof. Pauly, MD E2, 4.5 ECTS Fr, 10-12
• Simulation-based Inference, Prof. Bürkner, MD E2, 9 ECTS Tue, 14-16; Thu, 10-12
• Statistics in Toxicology I (Modelling), Prof. Rahnenführer, MD E2, 4.5 ECTS
• Econometrics, Prof. Demetrescu, MD E2, 9 ECTS Tue, 16-18; Thu 10-12
• Time Series Analysis, Jentsch, MD E1 Tue, 10-12; Wed, 8-10

Department of Mathematics

• Introduction to Computational Fluid Dynamics, Prof. Kuzmin, MD E1, 5 ECTS Mo, 10-12
• Numerical Methods for PDEs, Prof. Turek, MD E1, 5 ECTS, Fr, 14-16
• Optimization, Prof. Buchheim, MD E1, 5 ECTS Thu, 10-12

Department of Computer Science

• Computer Vision, Prof. Find, MD E1, 4 ECTS Tue, 14-16
• Programming Deep Learning Prof. Harmeling, MD E1, 8 ECTS Mon, 10-12; Wed, 10-12
• Theoretical Foundations of Machine Learning, Prof. Kamp, MD E1, 6 ECTS
• Verification of Neural Networks, Prof. Neider, MD E1, 6 ECTS Tue, 12-14
• Deep Reinforcement Learning, Prof. Peitz, MD E1, 8 ECTSTue, 10-12, Wed, 8-10
• Human-Centered Machine Learning, Prof. Mayer, MD E1, 6 ECTS Wed, 16-18

• Data Science for Dynamical System, 6 ECTS, Methods

   

Department of Economics

• Game Theory, Prof. Kramm, MD E2, 7.5 ECTS Mon, 8-12
• Data and AI in Economics, Prof. Posch, MD E2, 7.5 ECTS Tue, 14-18

Statistics

• Statistical Theory, MD 2
• Data Science in Context, MD 3
• Statistical Learning for Big Data, MD 5. For MD 5, you have to take this Course
• Panel Data Analysis I, 4.5 ECTS, Methods
• Natural Language Processing, 9 ECTS, Methods or Applications, by choice
• Bootstrap Methods, 9 ECTS, Methods
• Econometric Forecasting, 9 ECTS, Methods
• Asymptotic Theory, 4.5 ECTS, Methods
• Nonparamaetric and Hihg-Dimensional Econometrics, 4.5 ECTS, Methods
• On the Theory and Practivce of Monte Carlos Simulations, 4.5 ECTS, Methods or Applications, by choice
• Applied Bayesian Data Analysis, 9 ECTS, Applications
• Industrial Data Science I, 4.5 ECTS, Applications
• Statistics in Toxicology II / Testing, 4.5 ECTS, Applications
• Survey Sampling, 4.5 ECTS, Methods

Computer Science

• Cyber-Physical System Fundamentals, 8 ECTS, Methods
• Theoretical Foundations of Machine Learning, 6 ECTS, Methods
• Abstraction in Machine Learning, 6 ECTS, Methods
• Data Science for Dynamical System, 6 ECTS, Methods

Mathematics

• Programming Course: Data Science with Python, 3 ECTS, MD 3
• Introduction to Deep Learning and its Applications, 5 ECTS Methods
• Numerical Methods for PDEs, 5 ECTS, Methods