Master of Applied Artificial Intelligence
2027 Deakin University Handbook
| Year | 2027 course information |
|---|---|
| Award granted | Master of Applied Artificial Intelligence |
| Course credit points | 16 |
| Deakin course code | S736 |
| Course version | 1 |
| Faculty | Faculty of Science, Engineering and Built Environment |
| Course information | For students who commenced from 2019 onwards |
| Campus | Offered at Waurn Ponds (Geelong), Online |
| Duration | 2 years full-time or part-time equivalent. Depending on your professional experience and previous qualifications you may be eligible for credit which could reduce your course duration. |
| Course map - enrolment planning tool | The course map for students commencing from Trimester 1 2027 will be available soon Course maps for commencement in previous years are available on the Course Maps webpage or please contact a Student Adviser in Student Central. |
| CRICOS code | 0100305 Waurn Ponds (Geelong) |
| Australian Qualifications Framework (AQF) recognition | The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9 |
Course sub-headings
- Course overview
- Indicative student workload
- Professional recognition
- Career opportunities
- Participation requirements
- Mandatory student checks
- Pathways
- Alternative exits
- Course learning outcomes
- Course rules
- Course structure
- Work experience
- Fees and charges
Course overview
In a world where artificial intelligence (AI) is reshaping industries, many companies are seeking to understand and harness this transformative technology. With Deakin’s Master of Applied Artificial Intelligence, you will develop the specialised knowledge and skills essential to design and develop software solutions powered by AI, preparing you for in-demand roles worldwide. Deakin is ranked #1 in the state of Victoria for computing and information systems median salary, and 92.9% of Deakin computing and information systems postgraduates found employment within four months.
Embrace the future of digital disruption as you explore AI technologies, including deep learning and reinforcement learning. Apply these algorithms in areas such as computer vision and speech processing, and experience practical learning using state-of-the-art software, robotics, virtual reality (VR), and cyber-physical systems in fully equipped labs and studios.
Indicative student workload
You can expect to participate in a range of teaching activities each week. This could include lectures, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.
Professional recognition
The Master of Applied Artificial Intelligence is professionally accredited with the Australian Computer Society (ACS). This course is recognised internationally for entry to professional practice by other accrediting bodies through the Seoul Accord.
In order to meet ACS requirements for professional membership, students must satisfy the completion requirements for the whole degree. In addition, ACS guidelines require that the following specific units are completed at Deakin or equivalent units undertaken within another ACS-accredited program: SIT720, SIT744, SIT770, SIT789, SIT796, SIT753, SIT764, SIT782, SIT723, SIT792, SIT791, SIT709.
Career opportunities
With artificial intelligence estimated to contribute up to $15.7 trillion to the global economy by 2030, *it's fast becoming the cornerstone to technological progress across industries. AI and machine learning specialists also rank among the top three fastest-growing roles worldwide.^ Businesses and organisations are increasingly recognising how AI can be harnessed to optimise their growth and operations. This means careers in AI are more exciting and varied than ever before.
Job opportunities are thriving everywhere from healthcare, to retail, to financial services, to transport and logistics – and they will only continue to grow as AI advances. Set yourself up with a career that holds an important place in the employment opportunities of tomorrow.
As a graduate, you will have the specialist knowledge to become a sought-after professional in a range of roles, including:
- AI technology software engineer
- API integration expert
- AI researcher
- data scientist
- language model trainer
- prompt engineer
- natural language processing engineer
- AI product manager
- AI ethicist
- AI architect
- machine learning engineer.
* PwC’s Global Artificial Intelligence Study: Exploiting the AI Revolution.
^ World Economic Forum, The Future of Jobs Report 2025.
Participation requirements
Elective units may be selected that include compulsory placements, work-based training, community-based learning or collaborative research training arrangements.
Reasonable adjustments to participation and other course requirements will be made for students with a disability. More information available at Disability support services.
Mandatory student checks
Any unit which contains work integrated learning, a community placement or interaction with the community may require a police check, Working with Children Check or other check.
Pathways
Pathways for students to enter the Master of Applied Artificial Intelligence are as follows:
- Graduate Certificate of Information Technology (S578) followed by a 12-credit-point Master of Applied Artificial Intelligence
- Graduate Certificate of Information Technology(S578) and Graduate Certificate of Artificial Intelligence (S536) followed by an 8-credit-point Master of Applied Artificial Intelligence
Pathway options will depend on your professional experience and previous qualifications.
Alternative exits
| Graduate Certificate of Artificial Intelligence (S536) | |
| Graduate Certificate of Information Technology (S578) | |
| Graduate Diploma of Artificial Intelligence (S636) |
Equipment requirements
The learning experiences and assessment activities within this course may require students to have access to a range of technologies beyond a laptop or desktop computer. For information regarding hardware and software requirements, please refer to the Bring your own device (BYOD) guidelines via the School of Information Technology website in addition to the individual unit outlines in the Handbook.
Course learning outcomes
| Course Learning Outcomes |
|---|
| Develop an advanced and integrated knowledge of the technologies of artificial intelligence, including deep learning and reinforcement learning, with detailed knowledge of the application of AI algorithms across a range of domains and applications including computer vision and speech processing. Design, develop and implement software solutions that incorporate novel applications of artificial intelligence. Apply advanced knowledge of artificial intelligence to the research and evaluation of AI solutions and provision of specialist advice. Design artificial intelligence solutions that incorporate safe ethical decision making. |
| Communicate in professional and other context to inform, explain and drive sustainable innovation through artificial intelligence and to motivate and effect change by drawing upon advances in technology, future trends and industry standards, and by utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences including specialist and non-specialist clients, industry personnel and other stakeholders. |
| Identify, evaluate, select and use digital technologies, platforms, frameworks, and tools from the field of artificial intelligence to generate, manage, process and share digital resources and justify digital tools selection to influence others. |
| Questions assumptions and seeks to uncover inconsistencies and ambiguities in information and judgements, critically evaluates their sources and rationales, to inform and justify decision making in the field of artificial intelligence. |
| Apply expert, specialised cognitive, technical, and creative skills from artificial intelligence to understand requirements and design, implement, operate, and evaluate solutions to complex real-world and ill-defined computing problems. |
| Apply reflective practice and work independently to apply knowledge and skills in a professional manner to complex situations and ongoing learning in the field of artificial intelligence with adaptability, autonomy, responsibility, and personal and professional accountability for actions as a practitioner and a learner. |
| Work independently and collaboratively within multidisciplinary environments to achieve team goals, contributing advanced knowledge and skills from artificial intelligence to advance the teams objectives, employing effective teamwork practices and principles to cultivate creative thinking, interpersonal adeptness, leadership skills, and handle challenging discussions, while excelling in diverse professional, social, and cultural scenarios. |
| Engage in professional and ethical behaviour in the field of artificial intelligence, with appreciation for the global context, and openly and respectfully collaborate with diverse communities and cultures. |
Note – From 2026, Deakin commenced introducing Graduate Attributes (GAs), which define the distinctive characteristics of a Deakin graduate. You may notice some courses still refer to Graduate Learning Outcomes (GLOs) during this transition period.
Course rules
The Master of Applied Artificial Intelligence is structured in four parts:
- Part A: Foundation Information Technology Studies (4 credit points)
- Part B: Fundamental Artificial Intelligence Studies (4 credit points)
- Part C: Mastery Applied Artificial Intelligence Studies (4 credit points)
- Part D: Applied Artificial Intelligence Capstone Studies (4 credit points)
To complete the Master of Applied Artificial Intelligence you must pass 16 credit points. This includes:
- DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in your first study period
- 15 credit points of core units
- 1 credit point of course elective units (level 7 SIT or MIS-coded units)
Most units are equal to one credit point. As a full-time student you will study four credit points per trimester and usually undertake two trimesters per year.
Students are required to meet the University's academic progress and conduct requirements.
Course structure
Part A: Foundation Information Technology Studies
You are required to complete four core units within Part A (these are essential units for this degree).
In your first trimester you must also complete a 0-credit point unit which are compulsory for all Deakin University degrees.
| DAI001 | Academic Integrity and Respect at Deakin (0 credit points) |
| SIT771 | Object-Oriented Development |
| SIT772 | Database Fundamentals |
| SIT773 | Software Requirements Analysis and Modelling |
| SIT774 | Web Technologies and Development |
Part B: Fundamental Artificial Intelligence studies
You are required to complete four core units within Part B (these are essential units for this degree).
| SIT720 | Machine Learning |
| SIT787 | Mathematics for Artificial Intelligence |
| SIT788 | Engineering AI Solutions |
| SIT799 | Human Aligned Artificial Intelligence |
Part C: Mastery Applied Artificial Intelligence studies
You are required to complete four core units within Part C (these are essential units for this degree).
| SIT744 | Deep Learning |
| SIT796 | Reinforcement Learning |
| SIT789 | Robotics, Computer Vision and Speech Processing |
| SIT770 | Natural Language Processing |
Part D: Applied Artificial Intelligence Capstone studies
You are required to complete three core units and one course elective unit within Part D.
| SIT753 | Professional Practice in Information Technology |
| SIT764 | Team Project (A) - Project Management and Practices (capstone) |
| SIT782 | Team Project (B) - Execution and Delivery (capstone) |
Plus 1 level 7 SIT or MIS-coded elective (1 credit point)
Work experience
You may have an opportunity to undertake a placement as part of your course. For more information, please visit deakin.edu.au/sebe/wil.
Other learning experiences
You may choose to use one of your elective units to undertake an internship or participate in an overseas study tour to enhance your global awareness and experience.
Course duration
You may be able to study available units in the optional third trimester to fast-track your degree, however your course duration may be extended if there are delays in meeting course requirements, such as completing a placement.
Fees and charges
Tuition fees will vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study, your study load and/or unit discipline.
Your tuition fees will increase annually at the start of each calendar year. All fees quoted are in Australian dollars ($AUD) and do not include additional costs such as textbooks, computer equipment or software, other equipment, mandatory checks, travel, consumables and other costs.
For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit our Current students website.
Further information
Contact Student Central for assistance in course planning, choosing the right units and explaining course rules and requirements. Student Central can also provide information for a wide range of services at Deakin. To help you understand the University vocabulary, please refer to our Enrolment codes and terminology page.