The course aims to give a solid introduction to the Bayesian approach tostatistical inference, with a view towards applications in data mining and machine learning. The course contents is a mix of theoretical concepts,computer exercises and exercise sessions. Such concepts as prior-to-posterior updating, Markov Chain Monte Carlo, Bayesian prediction, marginalization of nuisance and many other concepts are studied in the course.