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Master of Applied Artificial Intelligence

Postgraduate coursework

Develop the specialist knowledge and skills necessary to design and develop software solutions that harness the latest advances in AI.

Key facts

Duration

The time and cost could be reduced based on your previous qualifications and professional experience. This means you can fast track the masters degree from 2 years down to 1.5 years, or even 1 year duration. See entry requirements below for more information.

Key dates

Direct applications to Deakin for Trimester 3 2024 close 27 October 2024

Current Deakin Students

To access your official course details for the year you started your degree, please visit the handbook

Course overview

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 around the globe.

Deakin’s Master of Applied Artificial Intelligence equips you with the specialist knowledge and skills necessary to design and develop software solutions that harness the latest advances in AI.

This course develops your understanding of AI technologies, deep learning, reinforcement learning and the application of these algorithms in computer vision and speech processing.

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 learn to apply advanced knowledge of artificial intelligence to the research and evaluations of AI and explore the complexities of introducing AI solutions in a human context, both from an ethical and an engineering 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.

As a graduate you will be well-equipped to work on design, development and operation of AI-driven software solutions.

Read More

Course information

Award granted
Master of Applied Artificial Intelligence
Year

2024 course information

Deakin code
S736
CRICOS code?
0100305 Waurn Ponds (Geelong)
Level
Higher Degree Coursework (Masters and Doctorates)
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, you will complete 8, 12 or 16 credit points, depending on your prior experience.

The course is structured in three parts:

  • Part A: Foundation Information Technology Studies (4 credit points)
  • Part B: Introductory Artificial Intelligence Studies (4 credit points)
  • Part C: Mastery Applied Artificial Intelligence Studies (8 credit points).

Depending upon prior qualifications and/or experience, you may receive credit for Parts A and B.

The course comprises a total of 16 credit points, which must include the following:

  • fifteen (15) credit points of core units
  • one (1) credit point of Level 7 SIT elective unit
  • DAI001 Academic Integrity Module (0-credit point compulsory unit).

Students are required to meet the University's academic progress and conduct requirements.

Core

Mandatory unit for all entry levels

  • Academic Integrity Module (0 credit points)
  • Part A: Foundation Information Technology Studies

  • Object-Oriented Development
  • Database Fundamentals
  • Software Requirements Analysis and Modelling
  • Web Technologies and Development
  • Part B: Introductory Artificial Intelligence Studies

  • Machine Learning
  • Mathematics for Artificial Intelligence
  • Professional Practice in Information Technology
  • Plus one level 7 SIT elective (one credit point)

    Part C: Mastery Applied Artificial Intelligence Studies

  • Deep Learning
  • Reinforcement Learning
  • Human Aligned Artificial Intelligence
  • Robotics, Computer Vision and Speech Processing
  • Engineering AI Solutions
  • Natural Language Processing
  • Team Project (A) - Project Management and Practices ~
  • Team Project (B) - Execution and Delivery ~
  • ~ 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.

    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)
      • Online

    Trimester 2 - July

    • Start date: July
    • Available at:
      • Waurn Ponds (Geelong)
      • Online

    Trimester 3 - November

    • Start date: November
    • Available at:
      • Waurn Ponds (Geelong)
      • Online

    Additional course information

    Other learning experiences

    You may choose to use one of your elective units to undertake an internship or participate in an overseas study tour to enhance your global awareness and experience.

    Course duration

    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.

    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.

    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.

    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.

    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 to be considered for selection, but this does not guarantee admission.

    Depending on your professional experience and previous qualifications, you may commence this course with admission credit and complete your course in 1 year full-time (or part-time equivalent).

    Academic requirements

    1 year full-time (or part-time equivalent) - 8 credit points

    To be considered for admission to this degree (with 8 credit points of admission credit applied) you will need to meet at least one of the following criteria:

    • completion of a bachelor degree (honours) (AQF 8) or higher in a related discipline
    • completion of a bachelor degree in a related discipline, and at least two years' of relevant work experience (or part-time equivalent)
    • Graduate Certificate of Applied Artificial Intelligence (or equivalent)

    1.5 years full-time (or part-time equivalent) - 12 credit points

    To be considered for admission to this degree (with 4 credit points of admission credit applied) 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' of relevant work experience (or part-time equivalent)
    • Graduate Certificate of Information Technology or equivalent

    2 years full-time (or part-time equivalent) - 16 credit points

    To be considered for admission to this degree (without admission credit applied*) you will need to meet the following criteria:

    • completion of a bachelor degree or higher in any discipline

    ^Recognition of Prior Learning into the Master of Applied Artificial Intelligence may be granted to students who have successfully completed appropriate postgraduate level studies.

    Related disciplines which may be considered include: cyber security, computing/computer science, information technology mathematics, design and analysis of algorithms, probability and statistics, database algorithm, information retrieval, web intelligence, machine learning.

    *Credit for recognition of prior learning will still be considered on a case-by-case basis. Learn more below.

    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:

    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.

    Recognition of prior learning

    The University aims to provide students with as much credit as possible for approved prior study or informal learning.

    You can refer to the Recognition of prior learning system which outlines the credit that may be granted towards a Deakin University degree and how to apply for credit.

    Fees and scholarships

    Fee information

    Estimated tuition fee - full-fee paying place
    $31,000 for 1 yr full-time - Full-fee paying place
    Learn more about fees and your options for paying.

    The available fee places for this course are detailed above. Not all courses at Deakin have Commonwealth supported places available.  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 fees and available payment options.

    FEE-HELP calculator

    What is FEE-HELP?

    FEE-HELP loans cover up to 100% of tuition fees for eligible students. By taking out a FEE-HELP loan, the government pays your tuition fees directly to Deakin, and the balance is repaid from your employment income - but only once you're earning over $51,550.

    Please note: fees shown by the calculator are indicative only and based on 2024 rates. Actual fees may vary. We advise confirming fees with Prospective Student Enquiries prior to enrolment.

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    • $* is the estimated full cost for a Master of Applied Artificial Intelligence (16 credit points), based on the 2024 fees.
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    *Disclaimer

    Deakin University (Deakin):

    • gives no warranty and accepts no responsibility for the currency, accuracy or the completeness of the information provided;
    • advises users that no reliance should be placed upon on the information provided, and;
    • instructs users that they should confirm the actual course fee with Prospective Student Enquiries prior to enrolment.

    This tool provides indicative information about the fees that will be payable in respect of courses and subjects offered to prospective students domiciled in Australia during the periods indicated.

    Please note that the fees shown by the calculator are indicative only and actual fees may vary. Users are advised to confirm the actual course fee with Prospective Student Enquiries prior to enrolment.

    The estimated course fee is based on the tuition fee costs applicable to a domestic full time student commencing the course in Trimester 1 and studying full time for the duration of the course but:

    • does not include non-tuition costs that may apply, such as Student Services and Amenities Fees (SSAF);
    • does not take into account any scholarships or bursaries awarded to the student (including the 10% Deakin alumni discount);
    • assumes the maximum number of units that need to be successfully completed actual number completed may be reduced if recognition of prior learning is granted;
    • assumes that no exceptional, or non-typical, circumstances apply to the proposed course of study;
    • assumes that the options that the user selects are appropriate for the course of study that they intend to undertake;
    • where fees are estimated for future years those fee will be subject to annual increases in accordance with increases in the cost of course delivery.

    Scholarship options

    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.

    Search or browse through our scholarships

    Postgraduate bursary

    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.

    Learn more about the 10% Deakin alumni discount

    Apply now

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    To apply, create an account in the Deakin Application Portal, enter your personal details and education experience, upload supporting documents and submit. Need help? Play this video, or contact one of our friendly future student advisers on 1800 693 888 or submit an online enquiry.

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    Entry pathways

    Contact information

    Our friendly advisers are available to speak to you one-on-one about your study options, support services and how we can help you further your career.

    Careers

    Career outcomes

    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.

    Professional recognition

    The Master of Applied Artificial Intelligence 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.

    Communication

    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.

    Digital literacy

    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.

    Critical thinking

    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.

    Problem solving

    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.

    Self-management

    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.

    Teamwork

    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.

    Global citizenship

    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