Knowledge Discovery and Data Mining (COMP5318)


Knowledge discovery is the process of extracting useful knowledge from data. Data mining is a discipline within knowledge discovery that seeks to facilitate the exploration and analysis of large quantities for data, by automatic and semiautomatic means. This subject provides a practical and technical introduction to knowledge discovery and data mining.
Objectives: Topics to be covered include problems of data analysis in databases, discovering patterns in the data, and knowledge interpretation, extraction and visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques: clustering, classification, prediction, estimation, affinity grouping, description and scientific visualisation

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Further unit of study information


Lecture 2 hrs/week; Tutorial 1 hr/week.


Through semester assessment (40%) and Final Exam (60%)


P.-N. Tan, M. l. Steinbach and V. Kumar/Introduction to Data Mining/2006/0-321-32136-7//

Faculty/department permission required?


Unit of study rules

Assumed knowledge

INFO9120 OR COMP5138

Study this unit outside a degree

Non-award/non-degree study

If you wish to undertake one or more units of study (subjects) for your own interest but not towards a degree, you may enrol in single units as a non-award student.

Cross-institutional study

If you are from another Australian tertiary institution you may be permitted to underake cross-institutional study in one or more units of study at the University of Sydney.