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 of data, by automatic or 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


(Lec 2hrs & Prac 1hr) per week


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

Faculty/department permission required?


Unit of study rules

Prerequisites and assumed knowledge

Assumed knowledge: COMP5138

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