Deep Learning Fundamentals

Postgraduate | 2026

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Area/Catalogue
COMP 5046
Course ID icon
Course ID
203317
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 course introduces key concepts underlying the development of deep learning techniques. These include: the place of deep learning in the context of statistics and machine learning; the definition, training and validation of deep models. A range of common models and their applications will be presented. The foundational ideas presented in this course will equip students to understand and interpret future developments in this fast moving field.

Course learning outcomes

  • Adapt and apply techniques to improve Neural Networks.
  • Apply strategies to design and implement a machine learning project using Deep Learning techniques.
  • Interpret future developments in Deep Learning based on core concepts presented.
  • Analyse Neural Network architectures including Convolutional Neural Networks.
  • Critically review and integrate Neural Network solutions to address real-life problems.

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A