This course covers machine-learning and data -mining concepts for analyzing very large, complex data sets Topics include data preprocessing, measuring data similarity, mining frequent patterns, association rule mining, classification/prediction, cluster analysis, neural-network, decision trees, discriminant analysis, rule-based decisions, nearest-neighbor and naive Bayes classifier, outlier detection and others. Machine learning tools like WEKA will be introduced to augment the course materials. Prerequisites: Consent of the instructor. (F;S)