Data Mining

CSCI-4390

This course will provide an introductory survey of the main topics in data mining and knowledge discovery in databases (KDD), including: classification, clustering, association rules, sequence mining, similarity search, deviation detection, and so on. Emphasis will be on the algorithmic and system issues in KDD, as well as on applications such as Web mining, multimedia mining, bioinformatics, geographical information systems, etc.

4 credits

Past Term Data

Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Spring Summer Fall
(Session 1) (Session 2)
2023
Data Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 0/90
2022
Data Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 65/90
2021
Data Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 63/90
2020
Data Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 38/60
2019
Data Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 43/70
2018
Data Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 37/70
2017
Data Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 44/70
2016
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 28/70
2015
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 27/70
2014
Database Mining (4c)
  • Wei Liu
Seats Taken: 13/65
2013
2012
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 27/40
2011
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 12/40
2010
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 18/40
2009
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 20/40
2008
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 9/40
2007
Database Mining (4c)
  • Mohammed J. Zaki
Seats Taken: 8/30