Master of Applied Artificial Intelligence (Professional)
Course summary for international students
| Year | 2026 course information |
|---|---|
| Award granted | Master of Applied Artificial Intelligence (Professional) |
| Campus | Offered at Waurn Ponds (Geelong), Online |
| Length | 2 years full-time |
| Fee paying annual fee - commencing 2026 | $44,200 for 1 yr full-time AUD |
| CRICOS code | 0100306 Waurn Ponds (Geelong) |
| Level | Higher Degree Coursework (Masters and Doctorates) |
| Deakin course code | S737 |
| 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
- Professional recognition
- Fees and charges
- Career opportunities
- Course learning outcomes
- Course rules
- Research information
- Course structure
- Admission criteria
- Academic requirements
- English language proficiency requirements
- Admissions information
- Pathways
- Credit for prior learning - general
- Alternative exits
- Workload
- Work experience
- Participation requirements
- Mandatory student checks
Course overview
In a world where artificial intelligence (AI) is reshaping industries, many companies are looking to understand and harness this transformative technology. With Deakin’s Master of Applied Artificial Intelligence, you will acquire the specialised knowledge and skills essential for designing and developing software solutions that leverage the power of AI. Get ready to graduate as an in-demand professional worldwide.
The Master of Applied Artificial Intelligence (Professional) extends the Master of Applied Artificial Intelligence by providing you with the opportunity to undertake industry-based learning or engage in an in-depth research project under the supervision of our internationally recognised research staff.
Are you ready to lead the charge in the AI revolution?
As an AI specialist, you will collaborate with multidisciplinary teams, including software engineers, data scientists, application developers, and business analysts, to ensure appropriate integration of AI into software solutions from a technical and human perspective.
Our world-leading research in AI feeds directly into our classrooms, meaning you will be learning at the cutting-edge of industry expectations and capabilities. Graduate with the hands-on experience to confidently work on the design, development, and operation of AI-driven software solutions.
Embrace the future of digital disruption and embark on a journey that immerses you in the realms of AI technologies, deep learning, and reinforcement learning. Explore the application of these algorithms in computer vision and speech processing, paving the way for innovative solutions across diverse sectors.
Artificial intelligence is driving digital disruption across almost every sector, redefining the workforce, and creating global demand for skilled professionals. There are projected to be more than 220,000 roles (25.3% growth or 44,700 new jobs) for software and application programmers in Australia in the next 10 years.^
With this significant projected job growth, now is the time to future-proof your career. By enrolling in our Master of Applied Artificial Intelligence (Professional), you position yourself at the forefront of this thriving field, equipped to drive innovation and shape the future of technology.
This course focuses on developing skills in data science, data modelling and design, machine learning, numerical analysis, programming and software development.
^ 2024 Employment Projections – for the ten years to 2034, Jobs and Skills Australia.
Professional recognition
The Master of Applied Artificial Intelligence (Professional) 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.
Fees and charges
The 'Estimated tuition fee' is provided as a guide only and represents the typical first-year tuition fees for students enrolled in this course. The cost will vary depending on the units you choose, your study load, the length of your course and any approved Recognition of prior learning you have.
One year full-time study load is typically represented by eight credit points of study. Each unit you enrol in has a credit point value. The 'Estimated tuition fee' is calculated by adding together eight credit points of a typical combination of units for your course.
You can find the credit point value of each unit under the Unit Description by searching for the unit in the handbook. Learn more about fees and available payment options.
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.^ Evidently, 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.
Course learning outcomes
| Deakin Graduate Learning Outcomes | Course Learning Outcomes |
|---|---|
| Discipline-specific knowledge and capabilities | 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. Have a broad appreciation of advanced topics within the IT domain through engagement with research or specialist studies. |
| Communication | 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. |
| Digital literacy | Identify, evaluate, select and use advanced 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. |
| Critical thinking | 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. |
| Problem solving | Demonstrate an advanced and integrated understanding of artificial intelligence and 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. |
| Self-management | 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. |
| Teamwork | Work independently and collaboratively within multidisciplinary environments to achieve team goals, contributing specialist 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. |
| Global citizenship | 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. |
Course rules
To complete the Master of Applied Artificial Intelligence (Professional), you must pass 8, 12 or 16 credit points. The number of credit points required may vary, depending on your entry point or how much credit you receive as recognition of prior learning (RPL) based on your professional experience and previous qualifications.
A 16-credit point Master of Applied Artificial Intelligence (Professional) includes:
- DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in their first study period
- Part A: Fundamental Applied Artificial Intelligence studies:
- 4 credit points of core units
- Part B: Mastery Applied Artificial Intelligence studies:
- 4 credit points of core units
- Part C: Specialisation or course electives
- 4 credit points which may comprise of:
- 4 credit point specialisation or
- 4 credit points of course elective units, level 7 SIT or MIS-coded
- 4 credit points which may comprise of:
- Part D: Professional studies which consists of:
- 4 credit points of professional studies 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.
All students are required to meet the University's academic progress and conduct requirements.
Research information
Students interested in pursuing a Higher Degree by Research (HDR), including a Masters by Research or PhD are encouraged to undertake the Professional Studies – Research Project pathway. High achieving students with a particular interest in research should also consider undertaking either the Research Training in Information Technology specialisation or additional research units as electives (e.g. SIT724, SIT746 and/or SIT747). Students are encouraged to contact Student Central and speak to a course adviser if they are interested in pursuing this option.
Course structure
Part A: Fundamental Artificial Intelligence studies
| DAI001 | Academic Integrity and Respect at Deakin (0 credit points) |
| SIT720 | Machine Learning |
| SIT787 | Mathematics for Artificial Intelligence |
| SIT788 | Engineering AI Solutions |
| SIT799 | Human Aligned Artificial Intelligence |
Part B: Mastery Applied Artificial Intelligence studies
| SIT744 | Deep Learning |
| SIT770 | Natural Language Processing |
| SIT789 | Robotics, Computer Vision and Speech Processing |
| SIT796 | Reinforcement Learning |
Part C: Specialisation or Course electives
A 4 credit point specialisation from the list below or 4 level 7 SIT or MIS-coded elective units (excluding SIT771, SIT772, SIT773 and SIT774).
Refer to the details of each specialisation for availability.
- Blockchain and Software Development
- Business Analytics
- Cyber Security
- Data Science
- Information Systems
- Information Technology Research Training
- Networking and Cloud Technologies
- Virtual Reality
Part D: Professional studies
Team Project
| 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 unit (1 credit point)
OR
Professional Practice
| STP710 | Career Tools for Employability (0 credit points) |
| SIT753 | Professional Practice in Information Technology |
| SIT764 | Team Project (A) - Project Management and Practices (capstone) |
| SIT791 | Professional Practice (2 credit points) * (capstone) |
OR
Research Project^
| SIT753 | Professional Practice in Information Technology |
| SIT764 | Team Project (A) - Project Management and Practices (capstone) |
Plus 1 unit (2 credit points) from the following:
| SIT723 | Research Techniques and Applications (2 credit points) + (research training capstone) |
| SIT792 | Minor Thesis (2 credit points) + (research training capstone) |
*Students undertaking this unit must have successfully completed STP710 Career Tools for Employability (0-credit point unit).
+ Entry is subject to specific unit entry requirements.
^Students interested in pursuing a Higher Degree by Research (HDR), including a Masters by Research or PhD are encouraged to undertake the Professional Studies – Research Project pathway. High achieving students with a particular interest in research should also consider undertaking either the Research Training in Information Technology specialisation or additional research units as electives (e.g. SIT724, SIT746 and/or SIT747). Students are encouraged to contact Student Central and speak to a course adviser if they are interested in pursuing this option.
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.
Admission criteria
Selection is based on a holistic consideration of your academic merit, work experience, likelihood of success, availability of places, participation requirements, regulatory requirements, and individual circumstances. You will need to meet the minimum academic and English language proficiency requirements or higher to be considered for selection, but this does not guarantee admission.
A combination of qualifications and experience may be deemed equivalent to minimum academic requirements.
Academic requirements
To be considered for admission to this degree you will need to meet at least one of the following criteria:
- completion of a bachelor degree or higher in a related discipline
- completion of a bachelor degree or higher in any discipline and at least two years' relevant work experience (or part-time equivalent).
Examples of related disciplines and relevant work experience include, but not limited to the broad field of Information technology.
English language proficiency requirements
To meet the English language proficiency requirements of this course, you will need to demonstrate at least one of the following:
- bachelor degree from a recognised English-speaking country
- IELTS overall score of 6.5 (with no band score less than 6.0) or equivalent
- other evidence of English language proficiency (learn more about other ways to satisfy the requirements)
Admissions information
Learn more about Deakin courses and how we compare to other universities when it comes to the quality of our teaching and learning.
Not sure if you can get into Deakin postgraduate study? Postgraduate study doesn’t have to be a balancing act; we provide flexible course entry and exit options based on your desired career outcomes and the time you are able to commit to your study.
Pathways
Pathways for students to enter the Master of Applied Artificial Intelligence (Professional) are as follows:
- Graduate Certificate of Information Technology (S578) followed by a 16-credit-point Master of Applied Artificial Intelligence (Professional)
- Graduate Certificate of Artificial Intelligence (S536) followed by a 12-credit-point Master of Applied Artificial Intelligence (Professional)
Pathway options will depend on your professional experience and previous qualifications.
Credit for prior learning - general
If you have completed previous studies which you believe may reduce the number of units you have to complete at Deakin, indicate in the appropriate section on your application that you wish to be considered for Recognition of prior learning. You will need to provide a certified copy of your previous course details so your credit can be determined. If you are eligible, your offer letter will then contain information about your Recognition of prior learning.
Your Recognition of prior learning is formally approved prior to your enrolment at Deakin during the Enrolment and Orientation Program. You must bring original documents relating to your previous study so that this approval can occur.
You can also refer to the recognition of prior learning (RPL) system which outlines the credit that may be granted towards a Deakin University degree.
Alternative exits
| Graduate Certificate of Artificial Intelligence (S536) | |
| Graduate Diploma of Artificial Intelligence (S636) | |
| Master of Applied Artificial Intelligence (S736) |
Course duration
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.
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.
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.
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.