Graduate Diploma in Artificial Intelligence and Machine Learning

Prosper through ‘thinking’ technology

Artificial intelligence and machine learning make life easier, in all its aspects: healthcare, defence, entertainment, agriculture. Artificial intelligence and machine learning now present the world’s single greatest commercial opportunity. Research indicates that by 2030 it could increase global GDP by up to 14%—a staggering US$15.7 trillion gain. Locally, hundreds of millions are invested towards industry-wide transformation, promoting significant job market growth.

Employment prospects are outstanding. AI and machine learning appointments worldwide have doubled in the past three years, with demand easily outstripping supply.

The Graduate Diploma in Artificial Intelligence and Machine Learning, conducted through the University of Adelaide’s world-renowned Australian Institute of Machine Learning (AIML), will prepare you to thrive in this exciting future.

What will you do?

Our Graduate Diploma in Artificial Intelligence and Machine Learning is driven by AIML’s cutting-edge research and extensive industry links, spanning diverse international sectors – from health, medical technology, defence and security to environment and natural resources.

In this graduate diploma you’ll undertake a carefully balanced mix of face-to-face intensive courses, work-integrated learning and online study. This degree will equip you with:

  • high-level technical skills in machine learning and AI application development, including in specialist areas, such as deep learning and visual question answering
  • broad awareness of the commercial, organisational and research opportunities presented by machine learning and AI
  • a deep understanding of the disciplines’ ethical and social considerations
  • the chance to gain valuable industry experience through an optional industry internship
  • extensive industry connections and networks.

You’ll also receive ongoing mentoring, feedback and direction from AIML’s world-class researchers and high-performing industry professionals.

How will you study?

This program is able to be studied in either part-time, standard full-time or accelerated mode—enabling you to undertake your studies at a pace and level of commitment that suits you. For further information, see the Degree Structure section.

Where could it take you?

You could help companies or public service providers provide unheard levels of personalised service. You might play a part in fully automating cities’ public transport systems for unprecedented reliability. Perhaps you’ll have a role in reducing the risk of skin sun damage with personalised AI risk monitoring technology.

Successful completion of the graduate diploma gives you advanced standing towards our Master of Artificial Intelligence and Machine Learning.



Advance your career in Artificial Intelligence and Machine Learning

AI is the new electricity of the 21st century. Unlock your next opportunity in this industry of the future, and study with the experts at the world-leading Australian Institute of Machine Learning.



  • Strong links with industry and research
  • Ranked #7 in the world for Artificial Intelligence#
  • Home of the world-leading Australian Institute of Machine Learning


#US News Best Global Universities, subject rankings, 2023

Entry Requirements

Choose your applicant type to view the relevant admissions information for this program.
I am a:

Before applying make sure you understand the eligibility and entry requirements for your chosen degree.

Look out for any prerequisites or assumed knowledge subjects. Some degrees also have additional entry requirements like interviews and auditions.

Domestic applicants

SATAC Code 3GD126, 3GD132
Deferment Yes - 2 year
Intake January, May and September
Prerequisites SACE Stage 2: Mathematical Methods . IB: Mathematics: Applications and Interpretations (HL) or Mathematics: Analysis and Approaches (SL) MathTrackX is an online bridging program available as a recognised alternative to Mathematical Methods.
Selection Criteria
Graduate entry

Higher Education Study A completed Bachelor's degree and a minimum GPA of 4.5

Fees and Scholarships

Choose your applicant type to view the relevant fees and scholarships information for this program.
I am a:

Domestic applicants

Indicative annual tuition fees
Commonwealth-supported place: $8,945

Where the standard duration of the program is less than one year the full cost of the program is displayed.

Successful domestic applicants to the Graduate Diploma of Artificial Intelligence and Machine Learning will have access to a limited number of Commonwealth Supported Places, meaning a reduction of up to 80% off the course fees due to government subsidies. Offer subject to change.

To apply for a Commonwealth Supported Place, please include SATAC code 3GD132 on your SATAC application.

Scholarships

These scholarships, as well as many others funded by industry and non-profit organisations, are available to potential and currently enrolled students.

Find a Scholarship.

Careers

Potential careers

Graduates of this program have gone on to roles such as:

Computational Scientist;  Computer Programmer;  Computer Scientist;  Diagnostic Technician;  Digital Strategist;  Software Specialist;  IT Manager;  IT Programmer

Degree Structure

The Graduate Diploma in Artificial Intelligence and Machine Learning is ideal for students who have a background/qualifications in any professional field and are looking to upskill in this exciting, high-demand area. The curriculum has been designed to include all of the necessary computer science foundations for students to succeed. Students with relevant qualifications or experience can apply for advanced standing*.

To qualify for the degree of Graduate Diploma in Artificial Intelligence and Machine Learning, students must satisfactorily complete a program of study consisting of the following requirements with a combined total of no less than 24 units comprising:

  • Three core courses to the value of 9 units

  • Up to five elective courses** to the value of 15 units

*For further information, please contact one of our friendly program advisors.

**Unless exempted, international students are required to take ENG 7057 Communication & Critical Thinking in lieu of an elective.


Study mode

This program is able to be studied in either part-time, standard full-time or accelerated mode—enabling you to undertake your studies at a pace and level of commitment that suits you*.

  • Accelerated mode – 12 units (4 courses) per trimester

  • Standard full-time mode – 24 units (8 courses) per year

  • Part-time mode – 3 or 6 units (1 or 2 courses) per trimester

You can even choose the study load that works best for you at different times of the year.

Whatever mode you choose, our interactive blend of online and face-to-face learning supports you in fitting your study around other commitments—without compromising on authentic and immersive learning experiences.

*International students please note: accelerated study modes are subject to visa conditions. Please contact one of our friendly program advisors for more information.

Academic Program Rules

The Calendar is a comprehensive handbook of the University's academic program rules.

Graduate Diploma in Artificial Intelligence and Machine Learning

Example Study Plan

Core course (9 units total)
Students must complete all of the following

Electives (15 units total)

Option 1:
5 courses* (3 units each)

OR

Option 2:
3 courses* (3 units each) plus ENG 7111 Internship (6 units)


*Unless exempted, international students are required to take ENG 7057 Communication & Critical Thinking in lieu of an elective.

Testimonial

The degrees structure uses the latest trends to build industry-ready graduates by introducing emerging technologies and policies and providing guidance to leverage their future.

The University of Adelaide is committed to regular reviews of the courses and programs it offers to students. The University of Adelaide therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

Last updated: Tuesday, 31 Oct 2023