Observational astrophysics produces large amount of very diverse data that have to be processed and then analyzed to derive properties of astrophysical objects with a given confidence. To do so, a good understanding of probability theory and mathematical statistics is necessary before addressing advanced methods such as time series analysis, clustering and machine learning. The class will alternate theoretical courses with tutorial sessions conducted in Python.

The key notions addressed in course include:
- Probability & Statistical inference
- Data smoothing
- Regression
- Multivariate analysis
- Time series analysis
- Clustering & classification