FIT3192 Emerging and advanced topics in artificial intelligence
Faculty of Information Technology
FIT3192 Emerging and advanced topics in artificial intelligence is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology. It isn't offered in 2027. It needs FIT2004 and FIT2111.
- Credit points
- 6
- Offered in 2027
- Not offered
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Requisites
Before FIT3192
Prerequisites
Pass these before you enrol.
After FIT3192
No unit lists FIT3192 as a prerequisite in the 2027 handbook.
Overview
This advanced undergraduate unit delves into the forefront of Artificial Intelligence, offering you an in-depth exploration of emerging and cutting-edge topics within the field. The course is designed to keep pace with the rapid advancements in AI, providing a comprehensive understanding of both foundational and innovative concepts.
Key topics covered in this course include 1) Multi-Agent Systems - Study the dynamics of systems where multiple autonomous agents interact, cooperate, or compete to achieve individual or collective goals; 2) Quantum Machine Learning - Investigate the intersection of quantum computing and machine learning and its potential applications in optimisation, cryptography, and complex data analysis; 3) Cognitive Systems - Examine AI systems that simulate human cognitive processes, including perception, reasoning, learning, and decision-making; and 4) Integrated Planning and Learning: Explore methods that combine planning and learning to enable AI systems to adapt and optimise their strategies in real-time with applications such as robotics, autonomous systems, and complex decision-making scenarios.
You will have a robust understanding of these advanced AI topics and be equipped with the knowledge to contribute to the development and application of innovative AI solutions in various domains.
Offerings in 2027
The 2027 handbook lists no offerings for FIT3192.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Demonstrate a comprehensive understanding of new concepts, techniques, and algorithms in the field of AI.
- 2
Compare and contrast different AI architectures, algorithms and advanced schemes using research-based knowledge and methods.
- 3
Evaluate the strengths and limitations of recent AI-driven technologies for industry application.
- 4
Understand the legal and ethical implications of AI on organisations and the future of work.
- 5
Apply technical writing and presentation to effectively communicate advanced topics in AI to a range of academic and expert audiences.
Where it fits
FIT3192 is part of 1 area of study in the 2027 handbook.
Contacts
- Chief Examiners
- Dr Vishnu Monn
Common questions
When is FIT3192 offered?
FIT3192 has no offerings listed in the 2027 handbook.
Which majors and minors include FIT3192?
FIT3192 is part of Artificial intelligence algorithms and models.
More details
- Credit points
- 6
- Level
- 3
- Study level
- Undergraduate
- Faculty
- Faculty of Information Technology
- Type
- Coursework
- EFTSL
- 0.125
- Student contribution
- SCA Band 2
- Study abroad
- Available
- Handbook years
- 20262027