COMP 337: Introduction to Data Mining

COMP 337, Fall 2010
Mon/Wed 09:00-10:20 Room 2053
Tutorials on Wed 17:00-17:50, Room 2406
 

Instructor  Qiang Yang (qyang@cse. ); Office: Room 3563, 2358-8768.  Office Hours: Tuesdays 1:30-3:00pm
Teaching Assistant: Sophie Si Shen  (shensi@cse.)  Office hours: Fridays 10:30-13:00.

Discussion Group: Course Newsgroup
Assignment Hand-in: email to TA.

Course Content:

Course Description

This course will provide an introduction to concepts and techniques in the field of data mining. Material include an introduction to data preprocessing and the techniques used to explore the large quantities of data for the discovery of predictive models and knowledge.  The course will include data mining techniques such as nearest neighbor, decision trees, neural networks, Bayesian networks and Na´ve Bayes, rule-based methods, association analysis and clustering, as well as social networks and data mining applications in business and finance applications.  We will also cover emerging data mining areas and applications. Students learn the material by attending lectures and implementing and applying different data analysis and data mining techniques to large datasets.

Topics:

Marking Scheme:

The course work includes assignments and projects, a midterm exam and a final exam.  The marking scheme is as follows.

Textbooks:

  Link to Qiang Yang's Homepage