C2005 Bachelor of Artificial Intelligence

The Bachelor of Artificial Intelligence develops students through a coherent sequence of AI foundation studies, AI specialist studies, practice studies, and elective-based domain pathways. 

Part A. Foundation studies 

AI foundation studies introduce programming, data and evaluation, technology impacts, and AI systems and tools, including secure and responsible use of AI-enabled systems.

Part B. Specialist studies 

AI specialist studies deepen capabilities in major areas of contemporary AI practice and advanced topics. You will choose from one of two specialisations Applied artificial intelligence or Artificial intelligence algorithms and models.

Part C. Practice studies 

Practice studies provide a structured, industry-embedded project spine through which students apply their knowledge in progressively more complex contexts, including project scoping, design, implementation, evaluation, governance, and capstone delivery.

Part D. Free elective studies

Electives will enable you to explore a range of options within the University. These units can be used to undertake majors offered across the Faculty, including areas such as agentic software engineering, cybersecurity, computer science, data science, games and interactive media, and others.

If you are in a double degree course, some units required for the partner degree are credited as electives towards the AI degree.

Course progression map 

The course progression map (Clayton) (Malaysia) provides guidance on unit enrolment for each semester of study.

This course comprises 144 points, of which 96 points must be from artificial intelligence study, and 48 points are used to provide additional depth or breadth through elective study.

The course develops through theme studies in: Part A. Foundation studies (24 points); Part B. Specialist studies (48 points); Part C. Practice studies (24 points); and Part D. Free elective study (48 points). 

Elective units may be at any level, however, no more than ten units (60 points) can be credited to the artificial intelligence course at level 1, and a minimum of 36 points must be completed in artificial intelligence at level 3. 

Note: Students at the Malaysia campus are required to complete an industry placement in order to graduate. This can be either the Industry-based learning unit (Part C) or the zero-credit-point unit FIT3199: Industry work experience. This unit will provide a framework for all undergraduate information technology students at the Malaysia Campus to complete the compulsory industry experience as required by the Malaysian Qualifications Agency. 

Units are 6 points unless otherwise stated. 

Part A. Foundation studies (24 points)

You must complete: 

• FIT1045 Software development 1: Programming foundations
• FIT1047 Computing systems 1: Foundations and operations
• FIT1059 Artificial intelligence: Concepts and tools for impact
• FIT1066 Responsible use of data in the age of AI

Part B. Specialist studies (48 points)

You must complete one of the following specialisations.

Applied artificial intelligence

You must complete: 

• FIT1056 Making with AI: Software in the AI era
• FIT2116 Artificial intelligence applications in context
• FIT2118 Artificial intelligence futures: Research directions, drivers and dangers
• FIT2131 Practical artificial intelligence application and development
• FIT3205 Applied computer vision
• FIT3206 Conversation for artificial intelligence
• FIT3207 Computing in practice: Leadership and influence
• FIT3226 Agentic and distributed AI: Multi-agent systems, swarms and artificial life

Artificial intelligence algorithms and models

If you have not completed VCE (Units 3 and 4) Mathematical Methods or Specialist mathematics, or equivalent, you must complete foundation unit: MTH1010 Functions and their applications. In the single degree, this unit is taken in place of a level 1 free elective. In a double degree, you will be required to increase the total credit points needed for the double degree by 6 credit points. A study overload will occur in Year 1 or 2 in consultation with the course director..

• MTH1010 Functions and their applications

You must complete: 

• MAT1003 Mathematics for algorithms and models
• FIT1061 AI algorithm foundations
• FIT2132 Reasoning with data
• FIT2115 Data structures and algorithms 1
• FIT2112 Deep learning
• FIT2111 Symbolic artificial intelligence and machine learning

You must complete two units from the following:

• FIT3191 Generative AI
• FIT3192 Emerging and advanced topics in artificial intelligence
• FIT3203 Embodied AI
• FIT3233 Optimisation and reinforcement learning

Part C. Practice studies (24 points) 

You must complete: 

• FIT2119 Computing in practice: Professional practice

AND either

a) AI in practice project units (18 points)

• FIT2120 Artificial intelligence  in practice: Project practices and management
• FIT3208 Artificial intelligence  in practice: Project 1
• FIT3209 Artificial intelligence  in practice: Project 2

OR

b) Industry-based learning placement (18 points)

FIT3045 Industry-based learning (IBL) unit is only available if you are selected to participate in the IBL placement program.

For Clayton students - If you are selected to participate in the IBL placement program you will complete FIT3045 Industry-based learning (18 credit points) and FIT2108 Industry-based learning (0 credit points); or FIT3045, FIT2108 and one of FIT3201 Industry-based learning onboarding (8 weeks) (0 credit points) or FIT3202 Industry-based learning onboarding (4 weeks) (0 credit points) (depending on the duration of your placement). This will replace the FIT3208 - AI in Practice: Project 1, FIT3209 - AI in Practice: Project 2 and FIT2120 AI in practice: Project practices and management.

For Malaysia students - Students at the Malaysia campus must complete an industry placement to graduate, as required by the Malaysian Qualifications Agency (MQA). This can either be FIT3045 Industry-based learning (if you are selected to participate) or FIT3199 Industry work experience. Note: You should complete FIT3199 over the Summer vacation period between the second and third year.

If you are selected to participate in the IBL placement program, you will complete the FIT3045 Industry-based learning (18 credit points) and FIT2108 Industry-based learning (0 credit points). This will replace three free electives (18 credit points).

All students in the IBL program must complete a unit over the summer semester or overload in one semester by one unit in order to complete the degree within three years (this is because you only complete 18 credit points of credit during the IBL placement semester). You must have completed at least three semesters of your course before starting your IBL placement.

Part D. Free elective studies (48 points)

Your elective units may be chosen from the Faculty of Information Technology, or from across the University; or you may choose to complete a major or minor from the Faculty of Information Technology or other courses, as long as you have the prerequisites and there are no restrictions on enrolment in the units.

Elective units may be at any level; however, no more than 10 units (60 points) at level 1 may be credited to your degree, and a minimum of 36 points must be at level 3.

If you are in a double degree course, some units required for the partner degree are credited as electives towards the AI degree.

You may complete one of the Flagship Rich Educational Experiences (FREE) units. These flagship rich educational experience units may be credited utilising your free electives if approved by the faculty. There are both 6 and 12 credit point unit options available.