2020 unit information
Classes and seminars in Trimester 2/Semester 2, 2020 will be online. Physical distancing for coronavirus (COVID-19) will affect delivery of other learning experiences in this unit. Please check your unit sites for announcements and updates one week prior to the start of your trimester or semester.
Last updated: 2 June 2020
Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit.
1 x 1 hour class per week, 1 x 2 hour practical per week.
1 x 1 hour scheduled online workshop per week.
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.
These are the Learning Outcomes (ULO) for this Unit
At the completion of this Unitsuccessful students can:
Deakin Graduate Learning Outcomes
GLO1: Discipline-specific knowledge and capabilities
GLO1: Discipline-specific knowledge and capabilitiesGLO3: Digital literacy
GLO1: Discipline-specific knowledge and capabilitiesGLO2: CommunicationGLO3: Digital literacy
demonstrate practical experience in critically exploring real world business data
GLO2: CommunicationGLO3: Digital literacyGLO4: Critical thinkingGLO5: Problem solvingGLO7: Teamwork
evaluate independently on self-directed learning tasks.
These Unit Learning Outcomes are applicable for all teaching periods throughout the year
The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.
The texts and reading list for the unit can be found on the University Library via the link below: SIT717 Note: Select the relevant trimester reading list. Please note that a future teaching period's reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester's prior year reading list as a guide only.
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