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COMP513 Data Mining

Updated: 02 November 2009
Credit Points 6
Offering
Responsible Campus Teaching Period Mode of Study Online Level
Armidale Semester 1 Off Campus D - Comp/internet essential
Armidale Semester 1 On Campus D - Comp/internet essential
ISBT Sydney ISBT Semester 1 On Campus D - Comp/internet essential
ISBT Sydney ISBT Semester 2 On Campus D - Comp/internet essential
ISBT Sydney ISBT Summer On Campus D - Comp/internet essential
Intensive School(s) None
Supervised Exam There is a UNE Supervised Examination held at the end of the teaching period in which you are enrolled.
Pre-requisites candidature in a postgraduate award
Co-requisites None
Restrictions COMP313
Notes

COMP389 or COMP589 desirable

Combined Units COMP313 - Data Mining
Coordinator(s) Paul Kwan (wkwan2@une.edu.au)
Unit Description

With the unprecedented rate at which data is being collected today, there is an emerging economic and scientific need to extract useful information from the data. Data mining is the process of automatic discovery of patterns in large data sets. This unit will provide an introduction to main topics in data mining and knowledge discovery, including association rules, classification, clustering, and online analytical processing. Emphasis will be placed on the algorithmic and systems issues, as well as the application of mining in real-world problems.

Materials Text information will be published prior to commencement of the teaching period.
Disclaimer Offer of some subjects is subject to viability. Information in these unit descriptions is subject to change prior to commencement of semester.
   

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