Deakin University
Master of Applied Artificial Intelligence (Professional)
- Delivery: Face to Face
- Study Level: Postgraduate
- Duration: 24 months
- Course Type: Master's
Expand your knowledge and skills to create innovative software solutions that utilize the latest advancements in AI.

Course overview
Many companies want to understand and harness this transformative technology in a world where artificial intelligence (AI) is reshaping industries. 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 allowing you to undertake industry-based learning or engage in an in-depth research project under the supervision of our internationally recognised research staff.
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 designing, developing and operating AI-driven software solutions.
Embrace the future of digital disruption and embark on a journey that immerses you in 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 will 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.
Key facts
July, 2026
What you will study
To complete the Master of Applied Artificial Intelligence (Professional), students must pass 16 credit points, which must include the following:
The course is structured in four parts:
- Part A: Fundamental Applied Artificial Intelligence studies (four credit points)
- Part B: Mastery Applied Artificial Intelligence studies (four credit points)
- Part C: Specialisation (four credit points) or level seven SIT or MIS-coded elective units (four credit points)
- Part D: Professional studies (four credit points).
The four parts comprise the following:
- Academic Integrity and Respect at Deakin (zero-credit-point compulsory unit)
- Eight credit points of core units
- Four credit point specialisation or 4 level 7 SIT or MIS-coded elective units (excluding SIT771, SIT772, SIT773 and SIT774)
- Four credit points of professional studies units.
Part A: Fundamental Applied Artificial Intelligence studies
- Academic Integrity and Respect at Deakin (zero credit points)
- Machine Learning
- Mathematics for Artificial Intelligence
- Engineering AI Solutions
- Human Aligned Artificial Intelligence
Part B: Mastery Applied Artificial Intelligence studies
- Deep Learning
- Natural Language Processing
- Robotics, Computer Vision and Speech Processing
- Reinforcement Learning
Part C Specialisation or level seven SIT
A four credit point specialisation from the list below or 4 level 7 SIT or MIS-coded elective units (excluding SIT771, SIT772, SIT773 and SIT774).
Please take a look at 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 (four credit points).
Team Project
- Professional Practice in Information Technology
- Team Project (A) - Project Management and Practices
- Team Project (B) - Execution and Delivery
Plus 1 level 7 SIT or MIS-coded elective unit (One credit point)
OR
Professional Practice
- Career Tools for Employability (zero credit points)
- Professional Practice in Information Technology
- Team Project (A) - Project Management and Practices
- Professional Practice (Two credit points)*
OR
Research Project
- Professional Practice in Information Technology
- Team Project (A) - Project Management and Practices
Plus 1 unit (Two credit points) from the following:
- Research Techniques and Applications (Two credit points)
- Minor Thesis (Two credit points)
Students undertaking this unit must have 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 Master's 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 advisor if they want to pursue this option.
Entry requirements
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 must 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 the 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:
- Completing a bachelor's degree or higher in a related* discipline.
- Completion of a bachelor's degree or higher in any discipline and at least two years' relevant* work experience (or part-time equivalent).
Related 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's 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).
Recognition of Prior Learning
Recognition of prior learning may be granted for relevant postgraduate studies, in accordance with standard University procedures.
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 and how to apply for credit.
Outcomes
Learning outcomes
- Develop an advanced and integrated knowledge of the technologies of artificial intelligence, including deep learning and reinforcement learning, with a detailed understanding of the application of AI algorithms across various domains and applications, including computer vision and speech processing.
- Design, develop and implement software solutions incorporating novel artificial intelligence applications.
- Apply advanced knowledge of artificial intelligence to research and evaluate AI solutions and provide 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.
- Communicate in professional and other contexts to inform, explain and drive sustainable innovation through artificial intelligence. Motivate and effect change by drawing upon advances in technology, future trends and industry standards and utilising a range of verbal, graphical and written methods. Recognise the needs of diverse audiences, including specialist and non-specialist clients, industry personnel and other stakeholders.
- 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 the selection of digital tools 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 artificial intelligence decision-making.
- Apply reflective practice and work independently to apply knowledge and skills professionally to complex situations and ongoing learning in 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 specialist knowledge and skills from artificial intelligence to advance the team's 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 artificial intelligence, with appreciation for the global context and openly and respectfully collaborate with diverse communities and cultures.
Career outcomes
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.
Fees and FEE-HELP
Estimated first-year tuition fee in 2026: $34,400 (domestic full-fee paying place).
All costs are calculated using current rates and are based on a full-time study load of eight credit points (normally eight units) per year.
A student’s annual fee may vary in accordance with:
- The number of units studied per term.
- The choice of major or specialisation.
- Choice of units.
- Credit from previous study or work experience.
- Eligibility for government-funded loans.
Student fees shown are subject to change. Contact the university directly to confirm.
FEE-HELP loans are available to assist eligible full-fee paying domestic students with the cost of a university course.