The course covers various data analysis methods using Bayesian statistics, with a focus on practical problem solving. We will go over a brief introduction to probability theory, Bayesian reasoning, and how to build a statistical model and compare it to data. The course builds towards analysing data from real astrophysical problems, using both classical statistical methods and machine learning.

This course sensitises doctoral students to ethical issues that may occur during their doctorate. After an introduction to ethics and good scientific practice, students are familiarised with resources that can assist them with ethical decision-making. Students get the chance to apply their knowledge in a context specific to research in electrical engineering and information technology.