Key facts
Duration
2 years part-time (includes the 11 month or 12 month pathway program via Great Learning and 1 year part-time Deakin content)
Locations
This course is delivered by Great Learning wholly Online.
New course from Trimester 3, 2026.
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.
Students who have successfully completed Great Learning’s Postgraduate Program in Machine Learning and Artificial Intelligence and who satisfy the entry requirements for this course will undertake further studies at Deakin.
Current Deakin students
To access your official course details for the year you started your degree, please visit the handbook
- Award granted
- Master of Applied Artificial Intelligence (Global)
- Year
2027 course information
- Deakin code
- S732
- Australian Qualifications Framework (AQF) recognition
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9
Course structure
To complete the Master of Applied Artificial Intelligence (Global) you must pass 12 credit points. This includes:
- DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in your first study period
- 10 credit points of core units
- 2 credit points of elective units
Students are required to meet the University's academic progress and conduct requirements.
Graduates of the Postgraduate Program in Artificial Intelligence and Machine Learning (PGPAIML) who have successfully completed Great Learning units equivalent to 6 credit points as recognised by Deakin; and will have met the minimum requirements for admission to Deakin, will be eligible for enrolment into the Deakin course with 6 credit points of Recognition of Prior Learning (RPL) and will be required to successfully complete 6 units with Deakin University in online mode in order to qualify for the Deakin Master of Applied Artificial Intelligence (Global) Award. i.e.
- 6 x Deakin units
- 6 x RPL
The Deakin component of the structure consists of all existing units which will be delivered online over a period of a year (3 x trimesters). Students will enrol part-time, undertaking 2 units (2 credit points) each trimester. Outlined below are the units.
You are required to complete 10 core units and two course elective units (these are essential units for this degree).
In your first trimester you must also complete a 0-credit point unit which is compulsory for all Deakin University degrees.
Recognition for prior learning (RPL) (based on Great Learning programs)
Totalling 6 credit points:
2 x level 7 course-grouped units
Deakin units
^ Recognition for prior learning (RPL) granted upon entry into the course
Intakes by location
The availability of a course varies across locations and intakes. This means that a course offered in Trimester 1 may not be offered in the same location for Trimester 2 or 3. Check each intake for up-to-date information on when and where you can commence your studies.
This course is only available to students via the Great Learning pathway. This course is not available to international students studying onshore in Australia. This course is offered part-time only.
Workload
You can expect to participate in a range of teaching activities each week. This could include classes, 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.
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 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.
To be considered for admission to this degree you will need to meet the following criteria:
- completion of a bachelor degree or higher in any discipline
Depending on your previous qualifications and professional experience, it may take you 1.5 years or 1 year to complete your 2 year masters degree (refer to Recognition for prior learning for additional information).
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)
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.
Fees and scholarships
Fee information
Fee rate
For fee information please refer to Great Learning
Apply now
Apply through Great Learning
Applications can be made directly to Great Learning. (Note this link is for Great Learning applicants based in India. It is unavailable when accessing from Australia). For more information on the application process and closing dates, please email Great Learning or call +91 804 718 7565.
Pathways
The Master of Applied Artificial Intelligence (Global) builds upon the postgraduate programs from Great Learning with units that extend students into the AI area. Units within the Deakin delivered content are independent of each other and will enable students to acquire the specialised knowledge and skills essential for designing and developing software solutions that leverage the power of AI.
Career outcomes
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.
Deakin's graduate learning outcomes describe the knowledge and capabilities graduates can demonstrate at the completion of their course. These outcomes mean that regardless of the Deakin course you undertake, you can rest assured your degree will teach you the skills and professional attributes that employers value. They'll set you up to learn and work effectively in the future.
| 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. Design artificial intelligence solutions that incorporate safe ethical decision making. |
| Communicate in professional and other contexts 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.
*Deakin references data from a range of government, higher education and reputable media sources. Learn more about our achievements on our University rankings page, or explore our sources page for supporting references.
