Customer Analytics in Large Organisations
Postgraduate
Postgraduate
INFS 5096
Postgraduate
Yes
Note: This offering may or may not be scheduled in every study period. Please refer to the timetable for further details.
154327
4.5
No
UniSA STEM
Apply analytic techniques to develop predictive models and behaviour pattern recognisers in the area of customer analytics.
Customer analytics: application of predictive modelling and behaviour pattern recognition techniques to perform customer base segmentation (breaking customers into groups with similar behaviour / propensity to buy / credit risk level / risk of committing fraud etc.) and predicting customer related outcomes (such as customer retention, response to marketing campaigns, present and future customer value etc)
Fraud and security analytics.
Credit Risk analytics.
Optimisation and Simulation.
Linear and non-linear programming.
Nil
Subject Area & Catalogue Number | Course Name |
---|---|
Group 1
Both courses: |
|
INFS 5100 | Predictive Analytics |
INFS 5102 | Unsupervised Methods in Analytics |
Nil
Component | Duration | ||
---|---|---|---|
INTERNAL, MAWSON LAKES | |||
Workshop (Face-to-face and/or virtual workshops, including small group work.) | 2 hours x 13 weeks | ||
Computer Practical | 1 hour x 12 weeks | ||
INTERNAL, CITY WEST | |||
Workshop (Face-to-face and/or virtual workshops, including small group work.) | 2 hours x 13 weeks | ||
Computer Practical | 1 hour x 12 weeks | ||
EXTERNAL, MAWSON LAKES, ONLINE | |||
External (On-line materials, on-line interactions with these material, weekly on-line computer practicals in a virtual machine environment, online interactions with the course coordinator and with other students, including through virtual workshops. ) | N/A x N/A |
Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.
Assignment, Problem solving exercise, Quantitative exercise
EFTSL*: 0.125
Commonwealth Supported program (Band 2)
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Fee-paying program for domestic and international students
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Non-award enrolment
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* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.