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1st for skills development for IT courses in Australia
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1st for learner engagement for IT courses in Australia
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1st for teaching quality for IT courses in Australia
Course information for - 2026 entry
- Duration
- 1.5 years full-time or equivalent part-time
- ATAR
- N/A
- Fees (first year)*
- Start dates
- Not on offer, ACU Term 3, ACU Term 4
Overview
Accelerate your career with a future-focused Master of Artificial Intelligence (MAI).
Artificial Intelligence is reshaping how we live, work, and connect from digital health and education to sustainability and ethical innovation. This distinctive program combines advanced technical expertise in machine learning, deep learning, and cloud-based AI systems with ACU’s mission-aligned emphasis on responsibility, human dignity, and the common good.
You’ll gain hands-on experience in applied AI, including generative models, natural language processing, and intelligent systems design, while developing the ethical, reflective, and leadership skills to ensure that AI technologies enable flourishing lives, thriving communities, and an ethical future.
Graduates will be prepared to lead innovation across industries, develop responsible AI strategies, and design intelligent solutions that address global challenges in health, sustainability, education, and society.
Careers
Graduates of the Master of Artificial Intelligence will be in demand across a wide range of industries where AI is driving transformation, including technology, healthcare, sustainability, education, finance, and public policy. You’ll graduate ready for roles such as:
- Artificial Intelligence / Machine Learning Engineer
- AI Product Manager or Research Scientist
- Data Scientist or Intelligent Systems Analyst
- Cloud or Edge AI Architect
- Responsible Innovation and Ethics Advisor
- Tech-for-Good / Social Impact Technologist
- AI Solutions Consultant or Digital Transformation Lead
- Digital Health or Sustainability AI Specialist
Whether leading technical teams, shaping policy, or designing next-generation AI systems, you’ll contribute to a future where technology supports human and planetary wellbeing.
Course details
Course structure
To qualify for the Master of Artificial Intelligence, a student must complete 120 credit points (cp).
Course map
Graduate statement
AQF framework
Exit Points
A student who has completed the requirements prescribed for the Graduate Diploma in Artificial Intelligence or Graduate Certificate in Artificial Intelligence may exit from the course with the relevant award.
Entry requirements
To be eligible for admission to the Master of Artificial Intelligence, applicants must comply with the Admission to Coursework Programs Policy.. To receive an offer, applicants must have completed one of the following:
1. An undergraduate degree in Artificial Intelligence, Computer Science, Information Technology or a related discipline* OR
2. An ACU Graduate Certificate in Artificial Intelligence OR
3. A Bachelor’s degree or higher qualification in any discipline and at least two years of relevant professional experience in a related discipline *OR
4. An Advanced Diploma or higher qualification in a related discipline* with at least five years of relevant professional experience.
*Related disciplines
Data Science, Software Engineering, Information Systems, Robotics, Electrical/Electronics or Computer Engineering, Cognitive Science, Networking, Programming, or Data Analytics, Machine Learning, Computer Vision, Natural Language Processing, or Intelligent Systems.
Disclaimer: The course entry requirements above are for 2026 Admission.
Inherent requirement
There are essential components of a course or unit that demonstrate the capabilities, knowledge and skills to achieve the core learning outcomes of that course or unit. You will need to be able to meet these inherent requirements to complete your course.
Learn more about inherent requirements for your course and how they affect you
Pathways
Pathways into course for applicants with previous study and/or life experience
Are you applying to ACU as a non-school leaver?
By that we mean, you’re not currently completing Year 12 and haven’t completed it in the two years previously. If the answer is yes and your selection rank isn’t enough to meet the requirements for your desired course you still have a number of options to help you achieve your study goals.
If you’re over 21, you can sit the Skills for Tertiary Admissions Test (STAT), or you can complete a diploma or bridging course relevant to your desired course.
Fees
Course costs
*This is an indicative first-year fee based on the tuition fee rates for a full-time student, using unit enrolment data from domestic students who studied the course in the previous year.
A student’s annual fee will vary depending on factors including:
- Number of units studied per year
- Choice of major or specialisation
- Elective units
The University reviews fees annually.
You can view current course costs and domestic tuition fee rates by unit.
Payment options
You should be able to concentrate on getting good marks instead of worrying about how you’ll pay your fees. We have a number of options that can help you ease the financial burden, including government assistance, scholarships and income support.
Scholarships
The University has allotted a total of 10 equity scholarships available for Computer Science students under the following categories:
- 5 scholarships for women in STEM - NextGen Women in STEM Pathways Scholarship - Australian Catholic University Scholarships
- 5 scholarships for Indigenous students - Indigenous Code and Data Scholarship - Australian Catholic University Scholarships
The scholarships are valued at $3,000 each and will be assessed by a panel chaired by the Office of the Provost. Applicants are required to submit a short written statement addressing the selection criteria.
In addition you could be eligible for one of the hundreds of scholarships we award each year to help students from across the university with the cost of studying, accommodation or overseas study opportunities. Some of our scholarships are awarded on the basis of merit, but these aren’t just for the academically gifted; ACU also recognises excellence in community engagement and leadership. We also offer a range of scholarships for those who may be struggling financially or who have faced other barriers to accessing education.
Apply for this course
ACU Online Applicants
Deferment
Deferment is available for one year. Find out more about deferment: Deferment Information.
Staff Profile
Associate Professor Eila Erfani
Program Director for the Computer and Data Science
Associate Professor Eila Erfani is the Program Director for the Computer and Data Science discipline at Australian Catholic University. She leads with a strong commitment to responsible innovation, high-impact research for social good, and future-focused teaching. Her work focuses on the ethical application of emerging technologies (e.g. AI) to address societal challenges and create meaningful human impact. Eila champions a user-centric approach to education that fosters both technical excellence and socially conscious, ethically grounded thinking.
Dr Mashud Rana
Senior Lecturer, Computer and Data Science
Dr Mashud Rana is a Senior Lecturer in Computer Science at the Australian Catholic University (ACU), with expertise in artificial intelligence (AI), machine learning (ML), and data science. Prior to joining ACU, Dr Rana was a Senior Research Scientist at CSIRO’s Data61 (2018–2024), where he led several nationally significant, cross-disciplinary projects focused on applying AI/ML to address challenges in energy, health, and environmental systems. In early 2025, he served as Assistant Director (Data Science) at the Australian Government’s Asbestos and Silica Safety and Eradication Agency, where he played a key role in developing AI governance and analytics to support national policy and risk management. Earlier in his career, he held Research Fellowships positions at the University of New South Wales (2015–2016) and the University of Sydney (2016–2018).
Dr Rana completed his PhD in Computer Science from the University of Sydney. His research interests include deep learning for time series and sensor data analytics, interpretable ML, information fusion, and AI-enabled decision support systems. He is passionate about bridging academia and industry through translational and collaborative research that delivers real societal impact.
Good Universities Guide 2024, undergraduate students, computing and information technology field