- 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.
For more information, please visit Data Literacy.
- Summer term 2022: Probabilistic Machine Learning