The aim of statistical learning theory is to study, in a probabilistic framework, the properties of learning algorithms. The purpose is two-fold: endow existing methods with performance guarantees, and suggest novel algorithmic approaches. This course gives a thorough introduction to the theory and methods of statistical learning theory, and in particular complexity regularization. This latter is at the heart of the most successful and popular machine learning algorithms today.