ITO5047 Fundamentals of artificial intelligence
Faculty of Information Technology
ITO5047 Fundamentals of artificial intelligence is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2020. It needs ITO4136, ITO4131 and ITO4137.
- Credit points
- 6
- Offered in 2020
- Not offered
This is the 2020 handbook entry. See the 2027 entry.
Reviews
No reviews yetNo reviews yet. Be the first to review ITO5047.
Requisites
Before ITO5047
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
After ITO5047
No unit lists ITO5047 as a prerequisite in the 2020 handbook.
Enrolment rules
Prerequisite knowledge:Â Fundamental math with introductory knowledge of probability
This unit is only available to students enrolled into C4009 Graduate Certificate of Computer Science, C5008 Graduate Diploma of Computer Science and C6008 Master of Computer Science.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit introduces the main problems and approaches to designing intelligent software systems including automated search methods, knowledge representation and reasoning, planning, reasoning under uncertainty, machine learning paradigms, and evolutionary algorithms.
Offerings in 2020
The 2020 handbook lists no offerings for ITO5047.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Explain the theoretical foundations of Artificial Intelligence (AI) - such as the Turing test, Rational Agency and the Frame Problem - that underpin the application to information technology and society;
- 2
Critically explain, evaluate and apply appropriate AI theories, models and/or techniques in practice - including logical inference, heuristic search, genetic algorithms, supervised and unsupervised machine learning and Bayesian inference;
- 3
Utilise appropriate software tools to develop AI models or software; and
- 4
Utilise and explain evaluation criteria to measure the correctness and/or suitability of models.
Workload and teaching
- Teaching approachOnline learning
A minimum of 122 hours over the 6 week teaching period should be used to complete assignments, participating in discussions, private study and revision.