This course will aim to provide the student with mathematical foundation and statistical knowledge of data mining and machine learning techniques. Particular focus will be on the fundamental statistical properties and analysis of many popular techniques for learning, classification and prediction. The topics covered in this course will include elements of the following:  Bayesian decision theory, model selection, linear Models for regression and classification, Bayesian networks, decision trees, association rule mining, and clustering.