COMP3009 (v.1) Data Mining
Area: | Department of Computing |
---|---|
Credits: | 25.0 |
Contact Hours: | 3.0 |
TUITION PATTERNS: | The tuition pattern provides details of the types of classes and their duration. This is to be used as a guide only. Precise information is included in the unit outline. |
Lecture: | 1 x 2 Hours Weekly |
Practical: | 1 x 1 Hours Weekly |
Anti Requisite(s): |
COMP5009 (v.1)
Data Mining
or any previous version
|
Prerequisite(s): |
STAT1002 (v.1)
Statistical Data Analysis
or any previous version
AND COMP1005 (v.1) Fundamentals of Programming or any previous version OR COMP1001 (v.1) Object Oriented Program Design or any previous version |
UNIT REFERENCES, TEXTS, OUTCOMES AND ASSESSMENT DETAILS: | The most up-to-date information about unit references, texts and outcomes, will be provided in the unit outline. |
Syllabus: | This unit will cover the key concepts of data mining with an emphasis on unstructured data analysis and interpretation. The first part of the unit covers the fundamental techniques used to pre-process unstructured data. Next, association rule mining concepts and techniques are reviewed and evaluated. Classification and cluster analysis is then covered in detail. Finally, stream data mining techniques are evaluated in the context of image and network traffic data analysis. |
Field of Education: | 020119 Artificial Intelligence |
Result Type: | Grade/Mark |
Availability
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