Welcome to the central page about UTS Master of Data Science and Innovation (MDSI). This page has been designed as a central area for all the aspects of MDSI, and the application process.
As you read through the information below, you will find many links to other areas of the UTS website which contain useful information. Please note you can always come back to this page to reorient yourself, and continue on your journey with this course.
Ready to Apply? Visit the how to apply page for important information and links to submit your application.
Ready for more details about the MDSI? The best place to hear from and speak to the teaching team, current MDSI students and to ask all your questions is at the next MDSI Information session for prospective students. Sign up here
About Master of Data Science and Innovation
The UTS Master of Data Science and Innovation is a ground-breaking program of study. It’s the first transdisciplinary data science degree offered in Australia where creativity and innovation are integral components. The MDSI equips students with the skills and expertise they’ll need for a rewarding career in data science and analytics.
Taking a transdisciplinary approach, the course utilises a range of perspectives from diverse fields and integrates them with industry experiences, real-world projects and self-directed study, equipping graduates with an understanding of the potential of analytics to transform practice. The course is delivered in a range of modes, including face-to-face learning and contemporary online experiences in UTS's leading-edge facilities.
Why Study MDSI?
Here are the five top reasons why you should choose to study the Master of Data Science & Innovation (MDSI) with UTS:
1. Learn by doing
This course is comprehensive, challenging students to gain essential knowledge in:
- core technical data science skills such as statistics, programming, machine learning and visualisation
- the social and ethical aspects of the profession
- and the creative elements of data science such as dealing with ambiguity and problem formulation.
2. Explore real problems with real data from Industry Partners
You will have the opportunity to work with industry partners and explore real-world projects with actual data sets and problems to solve. MDSI graduates are equipped with both communication and problem solving skills as well as interesting and challenging project experiences to share with potential employers.
Professional experience is part of the admission requirement for MDSI, which means during the course you will collaborate and build a community with students who have a wide range of skills and professional backgrounds. Many students have found the opportunity to connect with and understand fields far from their own the most valuable aspect of the program. The MDSI course also provides flexibility to shape your own data science path. The design of the assessments allows students to pursue their own particular interests and career aspirations.
4. Human-centred perspective on data
The course trains students to develop a human-centred perspective on big data; the ability to think ethically and critically about the wider implications of their models and their responsibility to ensure that they are used in an ethical manner.
5. Innovation and Creativity
The MDSI is the only transdisciplinary data science degree offered in Australia where creativity and innovation are integral components. Students develop creative thinking skills to confront contemporary challenges through working on complex, real-world data problems. They are encouraged to explore ideas freely and push the boundaries of their capabilities while considering the human perspectives of the situation. MDSI graduates develop the skills to source, frame, analyse, visualise and communicate business outcomes and generate creative data-driven solutions.
If you start in our Autumn session intake, this course is offered on a two-year, full-time or four-year, part-time basis.
If you start in our Spring session intake, this course is offered on a two-and-a-half-year, full-time basis or four-to-five-year, part-time basis (dependent on the number of subjects undertaken each session).
When are classes held?
The MDSI is designed with flexibility in mind. Classes are held after 6pm and all day Saturdays. They’re also not held every week, so a typical subject may have three evenings (6-9pm) and two Saturdays (9am - 5pm) sessions over the semester.
A full- time load is three subjects, so it is possible to schedule class around full- time work. What students usually find the most challenging is finding time for assessments and other pre-class work, which is often why students elect to study part- time.
Applicants must address all 3 of the following criteria:
1. Academic qualifications considered:
- Bachelor degree
- Graduate diploma
- Graduate certificate
- Masters degree
- Doctoral degree
2. The above qualifications may be in one of the following related disciplines:
- Mathematical Sciences
- Computer Science
- Physics and Astronomy
- Engineering and related technologies
- Banking, Finance and Related Fields
- 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.
The English proficiency requirement for international students or local applicants with international qualifications is: Academic IELTS: 6.5 overall with a writing score of 6.0; or TOEFL: paper based: 550-583 overall with TWE of 4.5, internet based: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64; or CAE: 176-184.
Eligibility for admission does not guarantee offer of a place.
For domestic students, cost information can be found by using the UTS Course Fee Calculator tool, and following the steps below:
- Choose 'Search for fees by course'.
- fee type 'Postgraduate Domestic Coursework'
- fee year 2020
- cohort 2020
- course area ‘Transdisciplinary Innovation’
- course code ‘C04372’
To calculate the total cost of the course, multiply the 'Total CP' by the ‘Fee per CP'.
Note: Commonwealth supported places are not available for MDSI.
If you do have to pay a fee and you're a local student, you may be eligible for FEE-HELP, an Australian Government loan scheme. Using FEE-HELP means you don't have to pay for your tuition fees up front. More information about FEE-HELP can be found at uts.edu.au/government-help-schemes
You can choose to repay your FEE-HELP loan simply by notifying your employer who will then withhold your payments through the PAYG tax system. You can also make payments directly to the Australian Taxation Office (ATO).
If you've already completed a degree at UTS then you're eligible for the Alumni Advantage program, which offers a 10% savings on full fee paying degree programs. Find out if you're eligible for Alumni Advantage at: alumni.uts.edu.au/advantage
If you’re an international student, head to uts.edu.au/international to find the course information, fees and application details relevant to you.
Students must complete 96 credit points (CP), comprising 56CP core and 40CP optional subjects. Optional subjects can be selected from specified data science related optional subjects and from across the University’s disciplines. Enrolment in subjects from other disciplines is dependent on approval from the Course Director and subject coordinator, and usually requires demonstrated ability to meet pre-requisites. This flexible course structure enables students to pursue their own particular interests and career aspirations.
For more detailed information on the course structure, and information on each of the below subjects visit our UTS Handbook.
96CP = 56CP Core Subjects + 40CP Optional Subjects
Core Subjects 56CP
- Data Science for Innovation 8cp
- Statistical Thinking for Data Science 8cp
- Data, Algorithms and Meaning 8cp
- Data Visualisation and Narratives 8cp
- iLab 1 12cp
- iLab 2 12cp
Optional Subjects (choose 40CP from the following*)
- Leading Data Science Initiatives 8cp
- Data and Decision Making 8cp
- Deep Learning 8cp
- Data Science Practice 8cp
- Elective 1 6cp
- Elective 2 6cp
- Elective 3 6cp
- Elective 4 6cp
Total Credit Points 96cp
* Please note the optional subject list is reviewed every year and is subject to change according to student demand.
Come Along to an Information Session
The next UTS MDSI information session for prospective students will take place on 20 November 2019 here on the UTS campus.
Information Sessions are free events for you to:
- Speak with Academics and students about the Master of Data Science & Innovation
- Receive information about the learning and teaching style of the course
- Receive career advice
- Ask questions