CS 331/295: Data Mining

Spring 2009

Time/Location: Monday and Wednesday 4:05pm to 5:20pm, Votey 367
Office hours: See the instructor's weekly timetable
Instructor

Xindong Wu
xwu@cs.uvm.edu
Prerequisites

One-semester programming in Java.
One-semester statistics/probability: STAT 153.
Textbook
Additional References


Course Description

Data mining is a broad area that integrates techniques from several fields including machine learning, statistics, pattern recognition, artificial intelligence, and database systems, for the analysis of large volumes of data. This course gives a wide exposition of these techniques and their software tools. Topics include: association analysis, classification, clustering, numeric prediction, pattern discovery in sequential data, and Bayesian networks.

Advanced Topics for PhD Comprehensive Exams
Grading Policy (in Spring '09)

Two Assignments: C4.5 due Feb. 4 and Weka due on Feb. 18 10%
Mid-Term Exam (close-book and close-notes): Monday, March 16 25%
Paper Presentations    15%
Essay 20%
Final Exam (close-book and close-notes): 3:30 PM - 6:30 PM, Thursday May 7; VOTEY 367 30%

Course Syllabus by Week

Useful Links


Comments to Xindong Wu (xwu@cs.uvm.edu)