IFSC 52503 - (was 5325) Data Mining Concepts and Techniques

Three hours lecture. Three credit hours.

Was IFSC 5325. In-depth, practical coverage of essential data mining topics, including knowledge discovery and the data mining process, data pre-processing, classification, and prediction, as well as cluster analysis. Will focus on popular and advanced data mining algorithms and models, including decision trees, support vector machines, neural networks, Bayesian networks, K-means, and density-based spatial clustering (DBSCAN). Advanced topics include information retrieval, text mining, social network analysis, and applications in several fields. Will use popular data mining software, allowing students a hands-on experience in mining data. Dual listed in the Undergraduate Catalog as IFSC 42503 (was IFSC 4325).

Prerequisites: IFSC 32003 (was IFSC 3320) or equivalent and graduate standing, or instructor consent.