Elect Engr & Computer Science - Introduction to Data Mining

Catalog description

This course studies algorithms and computational paradigms to discover knowledge in large and complex datasets. The course explains the fundamental principles, technical details, and real-life applications of data mining techniques through lectures, case studies, and hands-on projects. The core topics to be covered include data preprocessing, classification models, cluster analysis, association analysis, anomaly detection, result evaluation and visualization. Prerequisite: EECS 330, EECS 461 or MATH 526, and MATH 290 or MATH 291.