This course exposes students to the theory and practical methods associated with the field of artificial intelligence (AI). Students will gain an appreciation for the philosophy, history and applications of artificial intelligence. They will gain an understanding of the functioning of core algorithms within AI, and skills in the application of software tools which implement those algorithms. Areas covered will include knowledge representation, logic and automated reasoning, search, and modelling uncertainty, with a particular emphasis on techniques associated with various areas of machine learning, including unsupervised, supervised and reinforcement learning. Students will also be required to consider the ethics associated with the development and deployment of AI technology within society, and understand the importance of factors such as fairness, safety and explainability.
For further information regarding the course please refer to the Course Outline found at the following link.
* excluding students enrolled in a Postgraduate Clinical Psychology, Professional Pathway Psychology or Professional Pathway Social Work program. For accredited program and student contribution information please visit our CSP page.
Note: Due to the Job-ready Graduates Package new funding clusters and contribution amounts will take effect in the 2021 academic year. Grandfathering arrangements will be in place for students who would see an increase in their contribution amounts. Under these arrangements, students who commenced their course of study before 1 January 2021 facing increased student contribution amounts for a unit, will instead have their student contribution and Australian Government contribution amounts remain as they were under the previous arrangements (with existing rates being indexed by CPI each year). If continuing students are enrolled in units that will see their student contribution amount lowered, their student contributions will be the lowered amount