Introduces and presents basic concepts of data mining, data mining techniques, models and applications. Topics include association rule mining, classification models, sequential pattern mining and clustering. Prerequisites: cumulative GPA of 4.50 or better over all major EECS courses (without second digit "5"); LE/EECS 2030 3.00 or LE/EECS 1030 3.00; LE/EECS 3101 3.00, LE/EECS 3421 3.00 and one of SC/MATH 2030 3.00 or SC/MATH 2930 3.00 or SC/MATH 1131 3.00. Previously offered as: LE/CSE 4412 3.00.
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