Applied Machine Learning

Postgraduate | 2026

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Area/Catalogue
COMP 5053
Course ID icon
Course ID
203324
Level of study
Level of study
Postgraduate
Unit value icon
Unit value
6
Course level icon
Course level
5
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No
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Note:
Course data is interim and subject to change

Course overview

This course surveys the practical application of machine learning in modern organisations and society. Case studies will be used to demonstrate current best practice as well as common pitfalls. You will learn processes for tool-selection based on requirements and available resources; verifying and validating discovered models and how to apply results in real environments; and information resources for tracking technological advances.

Course learning outcomes

  • Understand when and why machine learning tools are used in industries.
  • Select an appropriate method and tool for a given problem and data set
  • Distinguish problems and data sets that are amenable to machine learning methods from those that are not
  • Analyse results and solutions to verify their correctness and identify sources of error
  • Compare the significance and validity of solutions obtained by multiple methods
  • Design data management procedures to enable accurate application of machine learning

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A