The Artificial Intelligence specialisation offers courses on a wide range of relevant topics. Depending on the chosen courses, students will learn about AI search, optimisation, reasoning, planning, diagnosis, machine learning, intelligent agents (reinforcement learning, information-theoretic foundations), data-driven approaches (matching and modelling), and bio-inspired computing (neural networks, and evolutionary algorithms).
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Demonstrate a solid understanding of a variety of Intelligence System (IS) approaches,
- Formalise real-world problems and select the most appropriate AI method to solve such a problem.
- Implement IS algorithms and design and carry out empirical evaluations.
Other Information
This specialisation is only available for students enrolled under the 2018 rules.If you enrolled before 2018, please select the appropriate year from the drop down box at the top right of the page.
Relevant Degrees
Requirements
This specialisation requires the completion of 24 units, which must consist of:
A maximum of 12 units may come from completion of courses from the following list:
| Code | Title | Units |
|---|---|---|
| COMP6260 | Foundations of Computing | 6 |
| COMP6262 | Logic | 6 |
| COMP6320 | Artificial Intelligence | 6 |
A minimum of 12 units must come from completion of courses from the following list:
| Code | Title | Units |
|---|---|---|
| COMP8420 | Bio-inspired Computing: Applications and Interfaces | 6 |
| COMP8600 | Introduction to Statistical Machine Learning | 6 |
| COMP8620 | Advanced Topics in Artificial intelligence | 6 |
| COMP8650 | Advanced Topics in Machine Learning | 6 |
| COMP8670 | Advanced Topics in Logic and Computation | 6 |
| ENGN6528 | Computer Vision | 6 |