Week Date Due Topic Chapters 1 Sep 07 Introduction 1 2 Sep 14 Proj1 Concept Learning 2 3 Sep 21 Proj2 Decision Trees 3 4 Sep 28 Proj3.1 Neural Networks (I) 4 5 Oct 05 Proj3.2 Neural Networks (II) 4 6 Oct 12 Bayesian Learning (I) 6 7 Oct 19 Proj4.1 Bayesian Learning (II) 6 8 Oct 26 Proj4.2 Evaluating Hypotheses 5 9 Nov 02 Proj5 Instance-based Learning 8 10 Nov 09 Proj6 Genetic Algorithms 9 11 Nov 16 Proj7 Rule Learning 10 12 Nov 30 Proj8 Analytical Learning 11 13 Dec 07 Proj9 Reinforcement Learning 13 14 Dec 14 Proj10 ** EXAM ** and Final Remarks