Graduate Diploma of Artificial Intelligence

2020 Deakin University Handbook

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Year

2020 course information

Award granted Graduate Diploma of Artificial Intelligence
Campus

This course is an exit option only

Cloud CampusNo
Duration1 year full-time or part-time equivalent
Deakin course codeS636
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 8.

Course sub-headings

Course overview

The Graduate Diploma of Artificial Intelligence is available as an exit option from the Master of Artificial Intelligence. The course provides you with an understanding of artificial intelligence, deep learning, reinforcement learning, and the application of these algorithms in computer vision and speech processing.

Career opportunities

Graduates will have the specialist knowledge needed to operate and engage with artificial intelligence across a broad range of industry sectors.

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. Click here for more information.

Course Learning Outcomes

Deakin Graduate Learning Outcomes

Course Learning Outcomes

Discipline-specific knowledge and capabilities

Develop an advanced 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.

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.

Global citizenship

Apply professional ethics, responsibilities, and norms of professional computing practice.

Approved by Faculty Board 14 March 2019

Course rules

To complete the Graduate Diploma of Artificial Intelligence, students must attain 8 credit points as detailed in the course structure.

The course comprises a total of 8 credit points, which must include the following:

  • 3 credit points of core units
  • 4 credit points from the Master of Applied Artificial Intelligence core units
  • 1 credit point Level 7 elective unit
  • 1 zero-credit point unit STP050 Academic Integrity

Students are required to meet the University's academic progress and conduct requirements. Click here for more information.

Course structure

Mandatory unit for all entry levels

STP050Academic Integrity (0-credit-point unit)

Part A: Introductory Artificial Intelligence Studies

SIT720Machine Learning

SIT787Mathematics for Artificial Intelligence

SIT719Security and Privacy Issues in Analytics

 

Part B: Mastery Applied Artificial Intelligence Studies

Select four units from the following:

SIT744Deep Learning

SIT796Reinforcement Learning ^

SIT799Human Aligned Artificial Intelligence

SIT789Applications of Computer Vision and Speech Processing

SIT788Engineering AI Solutions

SIT764Team Project (A) - Project Management and Practices

Plus one elective unit

^ Available from 2021


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.