An exploration of machine learning algorithms to find patterns in large datasets. Topics include classification, clustering, anomaly detection, and association analysis. Three lecture hours a week for one semester. May not be counted toward a degree in computer science. May be repeated for credit when the topics vary. Prerequisite: Computer Science 313E, 314, or 314H with a grade of at least C-.