C3002 · Monash University · UG specialist

Bachelor of Artificial Intelligence Advanced (Honours)

Faculty of Information Technology

Minimum ATAR: 80
Full time: 4 years
Part time: 8 years
Credit points: —
Campus: —
Mode: On campus

First-year units

Level 1 units every student in this course takes or chooses from.

FIT1045Software development 1: Programming foundationsProgramming is not just about writing code; it is about learning how to turn ideas and problems into clear, reliable instructions that a computer can execute. This unit introduces programming through computational thinking, algorithm design…
FIT1047Computing systems 1: foundations and operationsEvery time you run a program, open a file, connect to a network, train a model, deploy a service, or launch a container, layers of computing systems are working beneath the surface. This unit helps you understand those layers and gives you…
FIT1066Responsible use of data in the age of AIThis unit explores the critical role of data in shaping AI systems, from how data is collected and governed to how it is transformed and interpreted to support analytical and machine‑learning workflows. You will examine what data is, where…
FIT1061Artificial intelligence algorithm foundationsThis unit introduces you to the field of Artificial Intelligence (AI) as a specialisation within Computer Science. It provides an overview of the foundations of AI, including the history, key concepts, and applications across diverse domain…
MAT1003Mathematics for algorithms and modelsMathematics gives computing its ability to model, optimise and reason about the world. This unit develops the calculus and linear algebra needed to understand how computational models work, how algorithms represent change, and how data, sys…
FIT1059Artificial intelligence: Concepts and tools for impactIn this hands-on unit, you explore how evolving technology, data, and artificial intelligence affect individuals, societies, organisations, and the environment. The unit is co-run by staff drawn from across the university who provide direct…

Course structure

Open a major, minor or specialisation to see its units.

Rules for completing this course

You must complete 192 credit points, of which 144 credit points must be from artificial intelligence study and 48 credit points are used to provide additional depth or breadth through elective study. Elective units may be at any level, however, no more than ten units (60 credit points) can be credited to the artificial intelligence advanced course at Level 1 and a minimum of 36 credit points must be completed at each of Level 3 and 4 (or higher). All students in the IBL program must complete a unit over summer semester or overload in one semester by one unit in order to complete the degree within four 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. 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.

Part A. Foundation studies

36 cp

You must complete the following units

FIT1045Software development 1: Programming foundations6 cp
FIT1047Computing systems 1: foundations and operations6 cp
FIT1066Responsible use of data in the age of AI6 cp
FIT1061Artificial intelligence algorithm foundations 6 cp
MAT1003Mathematics for algorithms and models6 cp
FIT1059Artificial intelligence: Concepts and tools for impact 6 cp

Part B. Specialist studies

60 cp

You must complete the following units

FIT2132Reasoning with data 6 cp
FIT2115Data structures and algorithms 16 cp
FIT2112Deep learning6 cp
FIT2111Symbolic artificial intelligence and machine learning6 cp
FIT3191Generative artificial intelligence 6 cp
FIT3192Emerging and advanced topics in artificial intelligence6 cp
FIT3203Embodied artificial intelligence6 cp
FIT3233Optimisation and reinforcement learning6 cp
FIT3226Agentic and distributed AI: Multi-agent systems, swarms and artificial life6 cp

Elective units

6 cp

You must complete one of the following Level 4 or 5 elective units

FIT5216Modelling discrete optimisation problems6 cp
FIT5239Deep tech entrepreneurship6 cp
FIT4008Reading unit6 cp
FIT4047Computational modelling and simulation6 cp
FIT5240Quantum computing6 cp

Part C. Practice studies

30 cp

You must complete FIT4048 and FIT4049 and either the AI practice units (18 credit points) or the Industry-based Learning placement (18 credit points).

FIT4048Computing in practice: Advanced project 16 cp
FIT4049Computing in practice: Advanced project 26 cp

AI Practice unit

18 cp

You must complete the following units

FIT3208Artificial intelligence in practice: Project 16 cp
FIT3209Artificial intelligence in practice: Project 26 cp
FIT2120Artificial intelligence in practice: Project practices and management6 cp

Industry-based Learning placement

18 cp

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

FIT3045Industry-based learning18 cp
FIT2108Industry based learning seminar0 cp
FIT3201Industry-based learning onboarding (8 weeks)0 cp
FIT3202 Industry-based learning onboarding (4 weeks)0 cp
FIT3199Industry work experience0 cp

Part D. Research studies

18 cp

Note: To progress to Honours you are required to maintain at least a distinction average (70%) throughout your course. If you do not meet this standard you will be required to transfer to Bachelor of Artificial Intelligence. You must complete the following units.

FIT5125IT research and innovation methods6 cp
FIT4045Computing research project 16 cp
FIT4046Computing research project 26 cp

Part E. Free elective studies

48 cp

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. 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 points unit options available. To enhance your IT studies the Faculty recommends the following majors and minors which can be taken as part of your free electives. Other IT minors are also available, check the Faculty Handbook pages.