Introduction to Statistical Machine Learning (PG)

Postgraduate | 2026

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Area/Catalogue
COMP 5044
Course ID icon
Course ID
203315
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.
Yes
University-wide elective icon
University-wide elective course
Yes
Single course enrollment
Single course enrolment
Yes
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Note:
Course data is interim and subject to change

Course overview

This is an introductory course on statistical machine learning that will present you with an overview of several essential principles, popular techniques, and algorithms in statistical machine learning, as well as examples of their applications. You will build skills in developing algorithms using basic machine learning principles and theory. After completing this course, you will understand how, why and when machine learning can be utilised in real-world situations.

Course learning outcomes

  • Apply basic concepts of machine learning and classic algorithms, such as Support Vector Machines, Neural Networks and Deep Learning.
  • Demonstrate an understanding of the basic principles and theory of machine learning necessary to develop algorithms.
  • Devise algorithms to solve real-world problems.
  • Perform mathematical derivation of presented algorithms.

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A