Master of Applied Artificial Intelligence (Professional)

2023 Deakin University Handbook

Note: You are seeing the 2023 view of this course information. These details may no longer be current. [Go to the current version]

Year	2023 course information
Award granted	Master of Applied Artificial Intelligence (Professional)
Course Map	The course map for new students commencing from Trimester 1 2023. Part C: Professional Practice Part C: Research Training, Project And Electives Part C: Research Project Part C: Team Project The course map for new students commencing from Trimester 2 2023. Part C: Professional Practice Part C: Research Training, Project And Electives Part C: Research Project Part C: Team Project Course maps for commencement in previous years are available on the Course Maps webpage or please contact a Student Adviser in Student Central.
Campus	Offered at Waurn Ponds (Geelong)
Online	Yes
Duration	2 years full-time or part-time equivalent
CRICOS course code	0100306 Waurn Ponds (Geelong)
Deakin course code	S737
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.

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.

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’ll 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.

Indicative student 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.

Professional recognition

The Master of Applied Artificial Intelligence (Professional) is provisionally 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 Diploma of Artificial Intelligence (S636)
Master of Applied Artificial Intelligence (S736)

Fees and charges

Fees and charges vary depending on your course, the type of fee place you hold, your commencement year, the units you choose 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. Further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods is available on our Current students fees 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. Have a broad appreciation of advanced topics within the IT domain through engagement with research or specialist studies.
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 (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:

Completion of STP050 Academic Integrity (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.

Specialisations

Refer to the details of each specialisation for availability

Course structure

Core

Mandatory unit for all entry levels

STP050

Academic Integrity (0 credit points)

Part A: Introductory Artificial Intelligence Studies

SIT720

Machine Learning

SIT787

Mathematics for Artificial Intelligence

SIT770

Natural Language Processing

SIT744

Deep Learning

SIT788

Engineering AI Solutions

SIT789

Applications of Computer Vision and Speech Processing

SIT796

Reinforcement Learning

SIT799

Human Aligned Artificial Intelligence

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

SIT753

Professional Practice in Information Technology

SIT764

Team Project (A) - Project Management and Practices ~

SIT782

Team Project (B) - Execution and Delivery

One (1) level 7 SIT elective (1 credit point)

STP710

Career Tools for Employability (0 credit points)

SIT753

Professional Practice in Information Technology

SIT791

Professional Practice (2 credit points)*

One (1) level 7 SIT elective (1 credit point)

SIT723

Research Training and Project (2 credit points)

SIT746

Research Project (Advanced) (2 credit points)^

SIT753

Professional Practice in Information Technology

SIT723

Research Training and Project (2 credit points)

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.

Work experience

You will have an opportunity to undertake a placement as part of your course.

Details of specialisations

Blockchain and Software Development

Campuses

Burwood (Melbourne)

Unit set code

SP-S000092

Overview

This specialisation introduces you to state-of-the-art blockchain technologies and allows you to explore various software platforms and tools used for large-scale data analysis. You will learn how to build software solutions using modern software engineering techniques and have the opportunity to choose to hone your studies in the design and development of cloud applications or blockchain technologies depending on your area of interest.

Units

SIT708

Mobile Application Development

SIT725

Applied Software Engineering

SIT728

Blockchain Technologies and Real-World Applications

SIT737

Cloud Native Application Development

Business Analytics

Campuses

Burwood (Melbourne), Online

Unit set code

SP-MDBS004

Units

MIS770

Foundation Skills in Data Analysis

MIS771

Descriptive Analytics and Visualisation

Plus 2 credit points from:

MIS772

Predictive Analytics

MIS714

People Analytics

MIS781

Business Intelligence and Database

Cyber Security

Campuses

Burwood (Melbourne), Online

Unit set code

SP-S000028

Overview

Develop skills in securing data, communications and infrastructure as well as investigating, analysing and providing solutions to computer crime. Students gain an understanding of problem solving, communication and technical capabilities related to Information Technology Security and the legal, regulatory and ethical contexts in which these skills are used. The security units provide a solid foundation in areas including information security, internet and network security, access controls and firewalls. In conjunction with work experience, the units prepare students towards certification as a Certified Information Systems Security Professional on completion of the CISSP exam administered by The International Information Systems Security Certification Consortium (ISC)2.

Units

SIT716

Computer Networks and Security

SIT704

Ethical Hacking

And two (2) units from the following:

SIT703

Computer Forensics and Investigations

SIT735

Application and Communication Protocol Security

SIT736

Identity, Access Management and Physical Security

SIT738

Secure Coding

SIT763

Cyber Security Management

Data Science

Campuses

Burwood (Melbourne), Online

Unit set code

SP-S000055

Overview

The Data Science specialisation has been designed to provide students the opportunity to undertake study and develop technical skills in key areas of data science and data analytics.

Units

SIT718

Real World Analytics

SIT720

Machine Learning

And two (2) units from the following:

SIT741

Statistical Data Analysis

SIT742

Modern Data Science

SIT743

Bayesian Learning and Graphical Models

SIT744

Deep Learning

SIT731

Data Wrangling

Information Systems

Campuses

Burwood (Melbourne), Online

Unit set code

SP-MDBS012

Units

MIS701

Digital Business Analysis

MIS761

Cyber Security Strategies

MIS770/MIS770A

Foundation Skills in Data Analysis ^*

MIS782

Value of Information

^*MIS770A unit code denotes the Start Anytime version

Networking and Cloud Technologies

Campuses

Burwood (Melbourne), Online

Unit set code

SP-S000021

Overview

Learn to take advantage of modern networking and cloud technologies in the development, deployment, and scaling of enterprise solutions.

Units

SIT706

Cloud Computing

SIT716

Computer Networks and Security

SIT727

Cloud Automation Technologies

and one of

SIT722

Software Deployment and Operation

SIT729

Software Architecture and Scalability for Internet of Things

SIT737

Cloud Native Application Development

Virtual Reality

Campuses

Burwood (Melbourne)

Unit set code

SP-S000083

Overview

Virtual Reality (VR) is an immersive digital environment that can replicate lifelike physical environments or portray a fictional artificial world, and makes the user feel they are immersed in that environment in real-life. These can be viewed through a head mounted display (e.g. Oculus Rift and HTC Vive), a smartphone based display (e.g. Google Cardboard) or by standing within a cube or dome showing 3D projections on every surface. VR allows users to interact with these environments and can also create additional sensory experiences including virtual touch through haptic technology, smell, taste and sound. There is a strong emphasis on creating content that will assist in shaping the future of education, training and entertainment.

Career Outcomes

Virtual Reality and Augmented Reality skills are in high demand across a range of industries and graduates may find employment as Virtual Reality Game Designers, Oculus Developers, Game Producers, 3D Designers and Gameplay Engineers to name a few.

Units

SIT758

Assembling Virtual and Augmented Reality Experiences

SIT755

Interactive Application Design for Virtual and Augmented Reality

SIT756

Development for Virtual and Augmented Reality

SIT757

Content Creation for Interactive Experiences

Course duration - additional information

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.

Contact Student Central

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.