2 years full-time
Artificial intelligence (AI) is driving digital disruption, with new technology helping redefine many industries. Many companies are looking to take advantage of recent advances in AI, which is creating a large demand for skilled professionals.
Deakin’s Master of Applied Artificial Intelligence (Professional) equips you with the specialist knowledge and skills necessary to design and develop cutting-edge software solutions that harness the latest advances in AI.
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.
Ready to drive digital disruption and harness the power of AI?
As an AI specialist, you will work alongside software engineers, data scientists, application developers and business analysts, applying your knowledge to ensure AI is appropriately integrated into software solutions from a technical and human perspective.
You will gain hands-on experience in the development of software solutions and the use and development of AI. Our world-leading research in AI feeds directly into our classrooms, meaning that you will be learning at the cutting edge of industry expectations and capabilities.
This degree develops your understanding of the AI technologies, deep learning, reinforcement learning and the application of these algorithms in computer vision and speech processing.
As a graduate you will be well-equipped to work on design, development and operation of AI-driven software solutions.Read More
- Award granted
- Master of Applied Artificial Intelligence (Professional)
2024 course information
- Deakin code
- CRICOS code?
- 0100306 Waurn Ponds (Geelong)
- Higher Degree Coursework (Masters and Doctorates)
- Approval status
This course is approved by the University under the Higher Education Standards Framework.
- Australian Qualifications Framework (AQF) recognition
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9.
To complete the Master of Applied Artificial Intelligence (Professional), students must attain 16 credit points, which must include the following:
The course is structured in three parts:
- Part A: Core Applied Artificial Intelligence Studies (8 credit points)
- Part B: Specialisation (4 credit points) or Level 7 SIT or MIS elective units (4 credit points)
- Part C: Professional Studies (4 credit points).
The course comprises a total of 16 credit points, which must include the following:
- DAI001 Academic Integrity Module Module (0-credit-point compulsory unit)
- eight (8) credit points of core units
- four (4) credit point specialisation or four (4) Level 7 SIT or MIS elective units (excluding SIT771, SIT772, SIT773 and SIT774)
- four (4) credit points of Professional Studies.
Students are required to meet the University's academic progress and conduct requirements.
Mandatory unit for all entry levels
Part A: Introductory Artificial Intelligence Studies
Part B: Specialisation or 4 Level 7 elective units
Plus a four (4 credit point) specialisation or 4 Level 7 SIT or MIS elective units (excluding SIT771, SIT772, SIT773 and SIT774)
Part C: Professional Studies
One (1) level 7 SIT elective (1 credit point)
One (1) level 7 SIT elective (1 credit point)
One (1) level 7 SIT elective (1 credit point)
*Students undertaking this unit must have successfully completed STP710 Career Tools for Employability (0-credit point unit)
~ Note: Students are expected to undertake SIT764 and SIT782 in consecutive trimesters. Students should seek advice from the unit chair if they are unable to complete SIT764 and SIT782 consecutively.
^ Entry to SIT746 is subject to specific unit entry requirements.
Refer to the details of each specialisation for availability
- Blockchain and Software Development
- Business Analytics
- Cyber Security
- Data Science
- Information Systems
- Networking and Cloud Technologies
- Virtual Reality
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.
Trimester 1 - March
- Start date: March
- Available at:
- Waurn Ponds (Geelong)
Trimester 2 - July
- Start date: July
- Available at:
- Waurn Ponds (Geelong)
Additional course information
Course duration may be affected by delays in completing course requirements, such as accessing or completing work placements.
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.
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.
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.
You may have an opportunity to undertake a placement as part of your course. For more information, please visit deakin.edu.au/sebe/wil.
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 course entry requirements to be considered for selection, but this does not guarantee admission.
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)
- completion of a Graduate Certificate of Information Technology or equivalent.
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)
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’re able to commit to your study.
Recognition of prior learning
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 system which outlines the credit that may be granted towards a Deakin University degree.
Fees and scholarships
Learn more about fees and your options for paying.
The 'Estimated tuition fee' is provided as a guide only based on a typical enrolment of students completing the first year of 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.
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 tuition fees.
A Deakin scholarship might change your life. If you've got something special to offer Deakin – or you just need the financial help to get you here – we may have a scholarship opportunity for you.
If you’re a Deakin alumnus commencing a postgraduate award course, you may be eligible to receive a 10% reduction per unit on your enrolment fees.
Applications can be made directly to the University through StudyLink Connect - Deakin University's International Student Application Service. For information on the application process and closing dates, see the How to apply web page.
- Graduate Certificate of Artificial Intelligence (S536)
- Graduate Diploma of Artificial Intelligence (S636)
- Master of Applied Artificial Intelligence (S736)
Graduates will have the specialist knowledge needed to operate as Data Scientists, AI Technology Software Engineers, AI Product Managers, AI Ethicist and grow into roles such as AI Architect.
The Master of Applied Artificial Intelligence (Professional) is professionally accredited with the Australian Computer Society (ACS).
Course learning outcomes
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.
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.
Prepare a range of technical and user-oriented documentation using adequate structure, terminology and context to address technical and non-technical audiences.
Convey information and instructions in a clear, concise and coherent manner using appropriate oral communication techniques and skills for a broad range of audiences.
Imagine, conceive, and represent ideas using IT conventions, modelling languages, and standards to reflect on complex artificial intelligence ideas and processes in an effective manner.Apply interpersonal skills to lead, proactively assist, contribute to ideas, respect opinions and value contribution made by others when working collaboratively with a wide range of stakeholders.
Identify, select and use a range of digital technologies and tools to generate, manage and share digital resources associated with advanced artificial intelligence concepts and solutions.
Independently and systematically locate information, evaluate its reliability, and use the information for design, problem solving and research purposes.Recommend and use appropriate practices and processes to ensure the security, integrity, safety and availability of digital resources.
In assessing complex artificial intelligence scenarios, critically evaluate arguments, hypothesis, systems and proposals to identify basic statements.
In assessing complex artificial intelligence scenarios, locate ambiguity and vagueness in arguments, requirements, and proposals to determine if ideas are reasonable, and identify information that may be contradictory, omitted, or not collected.In assessing complex artificial intelligence scenarios, apply judgement in evaluating ideas, associated reasoning, and available evidence to arrive at conclusions that are valid.
Apply expert, specialised technical skills, knowledge and techniques to identify and define complex problems utilising advanced artificial intelligence in a variety of contexts.
Apply expert, specialised technical skills and knowledge in modelling methods and processes to understand problems, handle abstraction and design novel artificial intelligence solutions.
Apply expert, specialised technical skills and knowledge to develop innovative and creative approaches and/or solutions in planning, designing, managing, evaluating and executing complex artificial intelligence projects.
Integrate knowledge of social, safety, legal and cultural aspects to solve problems in complex and contradictory situations.
Evaluate own knowledge and skills with relation to wider artificial intelligence community and use frameworks of reflection to define and progress professional goals.
Recognise the need, and engage in, independent learning for continual development pf specialist knowledge and skills in artificial intelligence as a computing professional.
Demonstrate the ability to accept responsibility for objectives, and work under broad direction, engaging in the feedback process independently to ensure outcomes are achieved.
Contribute specialist knowledge and skills of artificial intelligence when working within a team, demonstrating high levels of responsibility and accountability.
Engage consistently and professionally in groupware to contribute expert knowledge and skills of artificial intelligence to achieve shared team objectives and outcomes.
Apply strategies to lead and support positive group dynamics, manage conflict and to function effectively as a team member.
Apply professional ethics, responsibilities, and norms of professional computing practice.
Demonstrate awareness of regulation and ethical implications of acquisition, use, disclosure and eventual disposal of information.
Engage with global trends and research with concern for societal, health, safety, legal, and cultural issues to effectively manage responsibilities relevant to artificial intelligence in practice.
Approved by Faculty Board 27 June 2019