Can we learn causal relationships from observations? In this 3-hour tutorial we attempt to give the intuition behind causal discovery from observational data, discuss the main assumptions, present the theory of Bayesian networks and some basic causal discovery algorithms, demonstrate some of their most successful applications to feature selection and biomedical data, and also share what the typical causal discovery enthusiast won’t tell you: what can go wrong.

Watch the tutorial, which was presented in ECML- PKDD 2011, here: http://videolectures.net/ecmlpkdd2011_tsamardinos_discovery/