Unsupervised Methods in Analytics
Postgraduate
Postgraduate
INFS 5102
Postgraduate
Yes
Note: This offering may or may not be scheduled in every study period. Please refer to the timetable for further details.
154324
4.5
No
UniSA STEM
To develop knowledge of the core techniques of unsupervised methods in data analytics, and to apply these techniques to large complex data sets using industry standard tool sets, such as SAS Enterprise Miner and Python.
Introduction to unsupervised methods; Cluster analysis; Association analysis; Applications of unsupervised methods: customer segmentation; anomaly detection; Advanced cluster analysis and association analysis; Advanced statistical programming.
Nil
Common to all relevant programs | |
---|---|
Subject Area & Catalogue Number | Course Name |
INFS 4020 | Big Data Concepts |
COMP 5070 | Statistical Programming for Data Science |
Nil
Component | Duration | ||
---|---|---|---|
INTERNAL, MAWSON LAKES | |||
Lecture | 2 hours x 13 weeks | ||
Computer Practical | 1 hour x 12 weeks | ||
INTERNAL, CITY WEST | |||
Lecture | 2 hours x 13 weeks | ||
Computer Practical | 1 hour x 12 weeks | ||
EXTERNAL, MAWSON LAKES, ONLINE | |||
External (Online materials, online discussion forum, online interactions with lecturer and other students, computer practicals) | 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, Skills demonstration, Test/Quiz
EFTSL*: 0.125
Commonwealth Supported program (Band 2)
To determine the fee for this course as part of a Commonwealth Supported program, go to:
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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.