Data Mining has emerged at the confluence of artificial intelligence, statistics, and databases as a technique for automatically discovering summary knowledge in large datasets. This course introduces students to the process and main techniques in data mining, including classification, clustering, and pattern mining approaches. Data mining systems and applications will also be covered, along with selected topics in current research.

Usually Offered:	Fall
Credit:	3 hours (class)
Prerequisite:	STAT 511 or equivalent, CS 381 or equivalent, or permission of instructor
Restriction:	[Proposed, offered as CS 590D in sem. 1 of 2007-08.]
University Catalog:	CS 573