Description
This subject focuses on advanced data mining techniques for intelligence informatics. It provides an in-depth coverage of the need for big data analysis, data warehousing, big data analytics, predictive methods, scalability considerations, data visualisation, and data mining techniques. Students will gain hands-on experience with various data mining tools and embedding … For more content click the Read More button below.
Other Requirements
Pre-enrolment Requirement
Text Requisites
Learning Outcomes
Upon completion of this subject, graduates will be able to:
1.
Explain the importance of big data analysis and data mining
2.
Identify and critically evaluate data mining techniques and tools
3.
Compare and evaluate appropriate techniques for clustering, classification and association rules mining
4.
Assess the potential benefits, risks, issues and challenges associated with big data and data mining
5.
Explore and analyse data mining patterns for intelligence informatics
Assessments
1. Written - Project report
2. Written - Examination (centrally administered)
3. Written - Research report
Offerings
Trimester 1
CAM-BNE-TR1
CAM-CNS-TR1
Trimester 1 Singapore
CAM-SIN-TR1S
Trimester 2
CAM-BNE-TR2
CAM-SIN-TR2
Trimester 3
CAM-BNE-TR3
Learning Activities
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