Unsupervised Methods in Analytics

Course aim

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.

Course content

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.

Textbook(s)

Nil

Prerequisite(s)

Subject Area & Catalogue Number	Course Name
Group 1 And one of the following courses;
INFS 4020	Big Data Concepts
INFS 3084	UO Big Data Concepts

Common to all relevant programs
Subject Area & Catalogue Number	Course Name
COMP 5070	Statistical Programming for Data Science

Corequisite(s)

Nil

Teaching method

Component	Duration
INTERNAL, MAWSON LAKES
Seminar	2 hours x 13 weeks
Computer Practical	1 hour x 12 weeks
INTERNAL, CITY WEST
Seminar	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.

Assessment

Assignment, Skills demonstration, Test/Quiz

Fees

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
International students and students undertaking this course as part of a postgraduate fee paying program must refer to the relevant program home page to determine the cost for undertaking this course.

Non-award enrolment
Non-award tuition fees are set by the university. To determine the cost of this course, go to:
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Not all courses are available on all of the above bases, and students must check to ensure that they are permitted to enrol in a particular course.

* 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.