Duration: 2 years full time; 4 years part time
Credit Points 96 (72CP in core subjects; 24CP in electives)
Course code: C04372
CRICOS code: 084268K (Autumn, 2 years); 093052G (Spring, 2.5 years)
Location: City Campus
This video gives you an idea of what it’s like to be a part of this world-leading program of study.
Students must complete 96 credit points (CP), comprising 72CP core and 24CP electives.
Electives can be selected from across the University’s disciplines, on approval from the Course Director and with demonstrated ability to meet pre-requisites, allowing students to pursue their own particular interests or build areas of strength.
How to apply
If you are an Australian or New Zealand citizen, Australian permanent resident or a humanitarian visa holder you can lodge your application quickly and easily online directly to UTS. Visit the UTS Postgraduate Admissions page to learn about how to apply and submit your application.
If your previous degree/s were completed overseas, please submit your application to Universities Admissions Centre (opens an external site) as UAC can verify your documents and calculate your GPA.
Prospective students are welcome to apply in their final semester of undergraduate study.
Closing dates for applications are subject to change - please refer to the Future Students Key dates page for updates.
If you are not an Australian or New Zealand citizen or Australian permanent resident, you will need to apply through UTS International.
Closing dates for applications are subject to change - please refer to the Information for International Students page for updates.
Recognition of Prior Learning
Students who have previously undertaken postgraduate study or completed an undergraduate degree at a university or other recognised tertiary education institutions may be eligible for Recognition of Prior Learning where subjects previously completed are found to be equivalent in regards to learning outcomes, content, volume of learning and assessment approaches.
A maximum of 12 credit points (two electives) can be submitted for consideration.
No automatic credit is given and applications must be made at the time of seeking admission into this course.
To be eligible for Recognition of Prior Learning, the subject being considered for prior study must have been completed within two years of commencing the course. Recognition of study completed before this period is not considered.
No core subjects are considered for recognition of prior learning.
For further MDSI recognition of prior learning details, consult the Master of Data Science and Innovation handbook.
To apply for recognition of prior learning, please follow the UTS recognition of prior learning.
Additional application requirements
All applicants must provide:
- a personal statement in which you explain (approx. 500 words) why you wish to study the course you are applying for, AND
- a CV, including details of paid and/or voluntary work or other experiences (eg. special interest groups) relevant to the course.
If you do not have a bachelor degree or higher qualification in a relevant discipline, you must also provide:
- a detailed explanation in your personal statement of prior learning and demonstrated capability with quantitative data skills, key mathematical concepts and programming experience, AND
- detailed evidence in your CV of prior learning and demonstrated capability with quantitative data skills, key mathematical concepts and programming experience.
Applicants must address all 3 of the following criteria:
1. Academic qualifications considered:
- Bachelor degree
- Graduate diploma
- Graduate certificate
- Masters degree
- Doctoral degree
2. Completed one of the listed academic qualifications with FOE in:
- 0101 – Mathematical Sciences
- 0201 – Computer Science
- 0103 – Physics and Astronomy
- 03 – Engineering
- 0801 – Accounting
- 0811 – Banking, Finance and Related Fields
- 0901- Economics and Econometrics
Applicants who hold other academic qualifications may be considered on the basis of general and professional qualifications that demonstrate their potential to the Master of Data Science and Innovation.
3. A minimum of three years professional/industry experience or demonstrated equivalent.
Test your statistics skills!
This test will help you determine your readiness for the 'statistical thinking for data science' subject, which is part of the Master of Data Science & Innovation course.