Graduate Diploma in Artificial Intelligence

What you will study

The course totals 48 credit points of study, comprising a 30-credit-point stream of core subjects, 12 credit points of artificial intelligence options and a six-credit-point professional option. Each subject is valued at six credit points.

Entry requirements

To be eligible for admission to this course, applicants must meet the following criteria.

Applicants must have one of the following:

• Completed Australian master’s or doctoral degree, or overseas equivalent, in Information Technology or Electrical and Electronic Engineering and Technology.
• Completed Australian bachelor's degree, graduate diploma, graduate certificate, or overseas equivalent in Information Technology or Electrical and Electronic Engineering and Technology with more than 75% of all subjects completed at pass level (conceded pass not included).
• Completed Australian bachelor's degree, graduate diploma, or graduate certificate, or overseas equivalent, in Information Technology with more than 70% of all subjects completed at pass level (conceded pass not included) AND A minimum of two years full-time, or equivalent part-time, Information Technology relevant post-secondary professional experience AND An interest in the course and demonstrated understanding of the opportunities present in Artificial Intelligence.
• Completed Australian associate degree, or overseas equivalent, in Information Technology with more than 75% of all subjects completed at pass level (conceded pass not included) AND A minimum of two years full-time, or equivalent part-time, Information Technology relevant post-secondary professional experience AND An interest in the course and demonstrated understanding of the opportunities present in Artificial Intelligence.
• Completed Australian advanced diploma, or overseas equivalent, in Information Technology AND A minimum of two years full-time, or equivalent part-time, Information Technology relevant post-secondary professional experience AND An interest in the course and demonstrated understanding of the opportunities present in Artificial Intelligence.

Supporting documentation to be submitted with the application

For applicants who need to demonstrate work experience, you need Curriculum vitae and a Statement of Service in one of the following formats:

• A 'Statement of Service' is provided by the employer.
• A completed 'UTS Statement of Service’ signed by the employer.
• A statutory declaration confirming work experience (for Australian residents only).
• An official letter from the applicant’s accountant or solicitor on their company letterhead confirming the applicant’s work experience or engagement with the business, duration of operations and the nature of the business.
• A business certificate of registration in the original language and English (e.g. provision of ASIC documentation or ABN or similar documentation for Australian businesses).

For applicants who need to demonstrate interest in the course, a Personal statement outlining the following:

• Capacity for postgraduate tertiary study.
• Previous paid or unpaid work and/or life experiences that are relevant to the proposed course of study.
• Demonstrated knowledge of the proposed course of study.
• Demonstrated awareness of expectations of the proposed course of study and its appropriateness to the applicant's needs.
• Demonstrated commitment to study.
• Other relevant experiences or information to support the application (e.g. evidence of any impact of disadvantages or inequity, experiences).

English language requirements

The English proficiency requirement for international students or local applicants with international qualifications is: IELTS Academic: 6.5 overall with a writing score of 6.0; or TOEFL iBT: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64 with a writing score of 50; or C1A/C2P: 176-184 with a writing score of 169.

Eligibility for admission does not guarantee an offer of a place.

Recognition of Prior Learning

Students may be eligible for up to a total of 24 credit points of subject exemptions based on Recognition of prior learning (RPL) as follows:

• Students who have completed equivalent subjects in a postgraduate program or UTS undergraduate program if the subjects previously completed are deemed by the faculty to be equivalent to subjects in the course.
• Subject exemption is applicable only to STM91715 Core stream (Artificial Intelligence).

Other/additional RPL may be granted via subject substitution to an alternative/advanced postgraduate subject in a similar field of study.

Students wishing to articulate from the Graduate Certificate in Information Technology (C11142) are advised to study the Data Analytics stream in the Graduate Certificate.

To be considered for recognition of prior learning, subjects must normally have been completed no more than ten years prior to the commencement of this course.

Outcomes

Learning Outcomes

Upon completion of this course, graduates will be able to:

• Graduates will use their knowledge of Indigenous Australian contexts to apply professional capabilities across the design and implementation of AI solutions in the industry when working with and for Indigenous peoples and communities.
• Graduates are able to identify a broad range of organisational stakeholders on Artificial Intelligence issues, and to identify ethical, personal, organisational, policy, social and environmental impacts of Artificial Intelligence in diverse contexts.
• Graduates are lifelong learners able to demonstrate autonomy and apply expert judgment in the design and evaluation of innovative Artificial Intelligence solutions to organisational, societal and global problems.
• Graduates are able to demonstrate and apply specialised knowledge in Artificial Intelligence and related fields of information technology, including technical skills in designing and implementing AI solutions incorporating current and emerging technologies.
• Graduates are able to communicate professionally in a variety of ways to specialist and non-specialist audiences and collaborate across functional, hierarchical and professional boundaries, within and across organisations, in local and global contexts.
• Graduates are able to work and thrive in the world of constant technological change by being self-reflective, curious, action-oriented, thoughtful and life-long learning professionals, dedicated to seeking feedback, applying well developed judgement, pursuing self-development and making a positive difference in organisations and the wider society.

Career Outcomes

Career options include: 

• Junior Analyst - Machine Learning
• Software Engineer - Machine Learning
• Junior AI Specialist
• Junior Data Analyst
• Junior Machine Learning Engineer

Fees and FEE-HELP

Estimated tuition fee per session in 2025: $18,615 (domestic full-fee paying place)

The estimated fee is calculated based on a study load of 24 credit points per session.

Tuition fees are charged:

• Based on the particular course in which you are enrolled.
• Based on the number of credit points you are enrolled in.
• At the rates set for the current year and revised annually.

In addition to tuition fees, students are required to pay a Services and Amenities Fee (SSAF). The purchase of textbooks and other course materials may also result in additional costs.

Student fees shown are subject to change. Contact the university directly to confirm.

FEE-HELP loans are available to assist eligible full-fee-paying domestic students with the cost of a university course.