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|Enrolment modes:||Trimester 2: Burwood (Melbourne), Cloud (online)|
|Previously coded as:||SCC717|
|Assumed Knowledge:||Knowledge appropriate to the topic.|
1 x 1 hour class per week, 1 x 2 hour practical per week
|Note: You will need to access substantial learning resources and experiences in CloudDeakin (Deakin’s online learning environment). Compliance with the Standards in computing, connectivity and student capability are a condition on your enrolment.|
The unit will begin with an introduction to the standard data mining processes such as CRISP-DM, then explain the requirements of business intelligence, in the context of customer relationship management. Methods to be taught in this unit include variants of association rule discovery (for basket analysis); prediction techniques such as inductive inference of decision trees and Bayes models (for market prediction), clustering techniques such as self-organization maps (for market segmentation), but with emphasis on real world applications. A selection of recent real world business intelligence case studies will be incorporated in this unit to illustrate the introduced techniques.
Projects (30%, 50%, 20%) 100%
Unit Fee Information
|Student Contribution Rate*||Student Contribution Rate**||Fee rate - Domestic Students||Fee rate - International students|
* Rate for all CSP students, except for those who commenced Education and Nursing units pre 2010
** Rate for CSP students who commenced Education and Nursing units pre 2010
Please note: Unit fees listed do not apply to Deakin Prime students.