Master of Applied Artificial Intelligence

2024 Deakin University Handbook

Year

2024 course information

Award granted Master of Applied Artificial Intelligence
Deakin course codeS736
Faculty

Faculty of Science, Engineering and Built Environment

CampusOffered at Waurn Ponds (Geelong)
OnlineYes
Duration

Depending on your professional experience and previous qualifications, your course will be:

  • 1 year full-time (2 years part-time) – 8 credit points
  • 1.5 years full-time (3 years part-time) – 12 credit points
  • 2 years full-time (4 years part-time) – 16 credit points
Course Map - enrolment planning tool

This course map is for new students commencing from Trimester 1 2024

This course map is for new students commencing from Trimester 2 2024

This course map is for new students commencing from Trimester 3 2024

Course maps for commencement in previous years are available on the Course Maps webpage or please contact a Student Adviser in Student Central.

CRICOS course code0100305 Waurn Ponds (Geelong)
Australian Qualifications Framework (AQF) recognition

The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9

Course sub-headings

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.

Indicative student 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.

Professional recognition

The Master of Applied Artificial Intelligence is professionally accredited with the Australian Computer Society (ACS).

Career opportunities

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.

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.

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.

Alternative exits

Graduate Certificate of Artificial Intelligence (S536)
Graduate Certificate of Information Technology (S578)
Graduate Diploma of Artificial Intelligence (S636)

Fees and charges

Fees and charges vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study and their study discipline, and your study load.

Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.

Use the Fee estimator to see course and unit fees applicable to your course and type of place. For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit our Current students website.

Course Learning Outcomes

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

Course rules

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.

Course structure

Core

Mandatory unit for all entry levels

DAI001Academic Integrity Module (0 credit points)

Part A: Foundation Information Technology Studies

SIT771Object-Oriented Development

SIT772Database Fundamentals

SIT773Software Requirements Analysis and Modelling

SIT774Web Technologies and Development

Part B: Introductory Artificial Intelligence Studies

SIT720Machine Learning

SIT787Mathematics for Artificial Intelligence

SIT753Professional Practice in Information Technology

Plus one level 7 SIT elective (one credit point)

Part C: Mastery Applied Artificial Intelligence Studies

SIT744Deep Learning

SIT796Reinforcement Learning

SIT799Human Aligned Artificial Intelligence

SIT789Robotics, Computer Vision and Speech Processing

SIT788Engineering AI Solutions

SIT770Natural Language Processing

SIT764Team Project (A) - Project Management and Practices ~

SIT782Team 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.

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.

Other 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.

Further information

Student Central can help you with course planning, choosing the right units and explaining course rules and requirements.