Artificial Intelligence
Master of Software EngineeringSpecialisation (formal)Year: 2025
Artificial Intelligence
Overview
Intended learning outcomes
Upon completion of this course, graduates will:
- Apply the mathematical principles used in machine learning and sequential decision marking;
- Design, implement, and evaluate artificial intelligence models for complex, real-world problems.
Last updated: 1 March 2025
Structure
50 credit points
The Artificial Intelligence specialisation is completed by undertaking 75 credit points of required study.
Note:
Students entering the course with advanced standing who plan on completing a specialisation may need to enrol in core specialisation subjects in their commencing semester. Please check and follow the structure outlined for your intended specialisation and seek course planning advice.
To obtain a specialisation in Artificial Intelligence, students must complete:
- 25 credit points of Year 2 core specialisation subjects
- 25 credit points of Year 3 Artificial Intelligence electives
Year 1
- 62.5 credit points of Year 1 compulsory subjects
- 12.5 credit points of Year 1 Software Engineering selectives
- 12.5 credit points of Year 1 Group A electives
- 12.5 credit points of Year 1 Group B electives
Year 2
- 75 credit points of Year 2 compulsory subjects
- 25 credit points of Year 2 core specialisation subjects
Year 3
- 50 credit points of Year 3 compulsory subjects
- 25 credit points of Year 3 Artificial Intelligence electives
- 25 credit points of electives including
- A minimum of 12.5 credit points of Software Engineering electives
- A maximum of 12.5 credit points of Approved electives
Progression:
The core subject lists are divided into specific year levels, reflecting the recommended order of completing the course. There is, however, some flexibility between Year 2 and 3 core subjects, depending on the requisites set between them. Check the individual Handbook entries of these subjects for more detail.
Subject options
Year 2 core specialisation subjects
Code | Name | Study period | Credit Points |
---|---|---|---|
COMP90049 | Introduction to Machine Learning |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90054 | AI Planning for Autonomy |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
(Must be completed in Year 2 of the course)
Year 3 Artificial Intelligence electives
Code | Name | Study period | Credit Points |
---|---|---|---|
COMP90042 | Natural Language Processing | Semester 1 (On Campus - Parkville) |
12.5 |
COMP90046 | Constraint Programming | Not available in 2025 | 12.5 |
COMP90050 | Advanced Database Systems |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90051 | Statistical Machine Learning |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
COMP90073 | Security Analytics | Semester 2 (On Campus - Parkville) |
12.5 |
COMP90083 | Computational Modelling and Simulation | Semester 2 (On Campus - Parkville) |
12.5 |
COMP90087 | The Ethics of Artificial Intelligence | Semester 1 (On Campus - Parkville) |
12.5 |
COMP90089 | Machine Learning Applications for Health | Semester 2 (On Campus - Parkville) |
12.5 |
COMP90090 | Text Analytics for Health | Semester 1 (On Campus - Parkville) |
12.5 |
ELEN90095 | AI for Robotics | Semester 2 (On Campus - Parkville) |
12.5 |
(Must be completed in Year 3 of the course)
Master of Software Engineering subject lists
Please see the main Master of Software Engineering page for remaining relevant subject lists.
Last updated: 1 March 2025