This course presents the main methods of data mining from the computer science perspective: supervised and unsupervised algorithms such as decision trees, naive Bayes, k-nearest neighbours, k-means,… and pattern mining (frequent item-sets, association rules, sequential patterns). The course also focuses on evaluation methods (confusion matrix, quality measures).