Teaching

Current courses

  • Summer term 2024: Probabilistic Machine Learning

The course provides an introduction to core concepts of machine learning from the probabilistic perspective.


Past courses

  • Summer term 2023: Machine Learning for Scientific Discovery

The seminar is for students who want to specialize in machine and deep learning methods to gain scientific insights. This year we focus on the whole-nervous-system understanding and the detailed neural circuit simulation of the fly (Drosophila), one of the most comprehensively understood organisms on the planet.

For more information, see Machine Learning for Scientific Discovery.

  • Winter term 2022/23: Data Literacy

This course equips students with concepts and tools for working with (large) data. Based on practical examples, we discuss frequently encountered problems alongside best practices. We cover basic statistical notions and problems of bias, testing and experimental design, and employ methods of machine learning and statistical data analysis to put these ideas in practice. We also discuss best practices for scientific data presentation and documentation and explore ethical and technical considerations in the context of fairness and transparency. The exercises will have a focus on practical programming.

  • Summer term 2022: Probabilistic Machine Learning