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Master of Data Science (ITM001.1)
Please note these are the 2024 details for this course
| Selection rank | English language requirements | Duration | UAC code |
|---|---|---|---|
| 2.0 years | 880261 | ||
| Faculty | Discipline(s) | Location | Available teaching periods |
| Faculty of Science and Technology | Academic Program Area - Technology |
Bruce, Canberra |
View teaching periods |
Fees
English language requirements
An IELTS Academic score of 6.5 overall, with no band score below 6.0 (or equivalent).
Fees disclaimer
Annual fee rates
The fees shown are the annual fee rates for the course. The annual rate is the fee that applies to standard full-time enrolment, which is 24 credit points. The final fee charged is based on the proportion of 24 credit points in which a student enrols. Students enrolled in a Commonwealth Support Place (CSP) are required to make a contribution towards the cost of their education, which is set by the Commonwealth Government. Information on Commonwealth Supported Places, HECS-HELP and how fees are calculated can be found here.
Please note: Course fees are assessed annually and are subject to change.
| Academic entry requirements | English language requirements | CRICOS code | Faculty |
|---|---|---|---|
| 099433A | Faculty of Science and Technology | ||
| Discipline(s) | Location | Available teaching periods | Duration |
| Academic Program Area - Technology |
Bruce, Canberra |
View teaching periods | 2.0 years |
Fees
Fees disclaimer
Annual fee rates
The fees shown are the annual fee rates for the course. The annual rate is the fee that applies to standard full-time enrolment, which is 24 credit points. The final fee charged is based on the proportion of 24 credit points in which a student enrols. Information on how fees are calculated can be found here.
Please note: Course fees are assessed annually and are subject to change.
English language requirements
An IELTS Academic score of 6.5 overall, with no band score below 6.0 (or equivalent).
Academic entry requirements
To study at UC, you’ll need to meet our academic entry requirements and any admission requirements specific to your course. Please read your course admission requirements below. To find out whether you meet UC’s academic entry requirements, visit our academic entry requirements page.
Be at the cutting edge of the digital world
Master your big-picture thinking and connect your digital understanding with data analysis, interpretation and management of complex data sets on a micro and macro level.
Large-scale data analysis and modelling underpin a vast range of industries, including healthcare, sports, business, scientific discovery, and government policy. With a Master of Data Science, you'll cement your place in one of the world’s most in-demand professions and gain the skills to become a leader within the field through a unique combination of interdisciplinary coursework, research methodology, and comprehensive industry-based training.
Become a specialist within the field with the option to specialise in Sports Analytics, Business Intelligence, Artificial Intelligence & Computational Modelling.
Study a Master of Data Science at UC and you will:
- Master your knowledge and skill to read and interpret Big Data
- Become proficient in using state-of-the-art industry tools
- Critically analyse databases and offer innovative solutions
- Expand your practice by working on real-world issues
- Learn and apply professional ethics, teamwork, critical analysis, communication and management skills
- Build strong industry networks
- Earn an industry-recognised and respected qualification
- Be in demand
Work Integrated Learning (WIL)
WIL is a key component of the Master of Data Science course delivery as it offers students the opportunity to apply their learnings into industry-based practice (both real and/or in-situ) and build their professional networks.
To ensure our students have access to the right people and places, UC works hard to foster close industry connections and regularly engages with industry partners who possess both the skills and experience to provide specialised knowledge and training opportunities.
All course content is reviewed annually by our Course Advisory Group which is made up of a panel of highly qualified and respected industry experts
Career opportunities
Due to the exponential rise of digital data produced daily around the world, graduates of the UC Master of Data Science course can expect to find themselves in high demand in any one of the following positions.
- Data scientist
- Data engineer
- Data analyst
- Business analyst
- Statistician
- Software developer
- Data warehouse operator and manager
- Computer network analyst
- Consultant
An Australian bachelor degree in any field or equivalent.
Assumed knowledge
Year 12 mathematics and functional knowledge of using computer systems.
Periods course is open for new admissions
| Year | Location | Teaching period | Teaching start date | Domestic | International |
|---|---|---|---|---|---|
| 2024 | Bruce, Canberra | Semester 1 | 05 February 2024 | ||
| 2024 | Bruce, Canberra | Semester 2 | 29 July 2024 | ||
| 2025 | Bruce, Canberra | Semester 1 | 03 February 2025 | ||
| 2025 | Bruce, Canberra | Semester 2 | 28 July 2025 | ||
| 2026 | Bruce, Canberra | Semester 1 | 02 February 2026 | ||
| 2026 | Bruce, Canberra | Semester 2 | 27 July 2026 |
Credit arrangements
There are currently no formal credit transfer arrangements for entry to this course. Any previous study or work experience will only be considered as part of the application process in accordance with current course rules and university policy.
Master of Data Science (ITM001) | 48 credit points
- Awards: To have a specialisation on his or her testamur, a student must complete all units listed in that specialisation. Otherwise, students can choose and mix the units as they prefer.
- 3 credit points of ITS units at G or PG level
In addition to course requirements, in order to successfully complete your course you must meet the inherent requirements. Please refer to the inherent requirements statement applicable to your course
UC - Canberra, Bruce
Year 1
Semester 1
Semester 2
One Restricted Choice Part B Unit (G or PG Level)
Year 2
Semester 1
One Restricted Choice Part A (G or PG Level)
Two Restricted Choices Part A (PG Level)
Semester 2
One Restricted Choice Part A (PG Level)
Year 1
Semester 2
Year 2
Semester 1
One Restricted Choice Part A Unit
One Restricted Choice Part B Unit (G or PG Level)
One Restricted Choice Part B Unit (G or PG Level)
Semester 2
One Restricted Choice Part A Unit
Three Restricted Choice Part A units
Year 3
Semester 1
Two Restricted Choice Part A units
One Restricted Choice Part A Unit
Course duration
Standard 2 years full-time, or part-time equivalent. Maximum duration - 6 years.
Learning outcomes
| Learning outcomes | Related graduate attributes |
|---|---|
| Develop advanced knowledge of data science principles, theory, concepts, and tools across the spectrum from data collection to analysis, modelling, interpretation, prediction, and communication; | UC graduates are professional: Employ up-to-date and relevant knowledge and skills; communicate effectively; use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems; work collaboratively as part of a team, negotiate, and resolve conflict; display initiative and drive, and use their organisational skills to plan and manage their workload; take pride in their professional and personal integrity. UC graduates are global citizens: Think globally about issues in their profession; adopt an informed and balanced approach across professional and international boundaries; understand issues in their profession from the perspective of other cultures; communicate effectively in diverse cultural and social settings; make creative use of technology in their learning and professional lives; behave ethically and sustainably in their professional and personal lives. UC graduates are lifelong learners: Reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development; adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas; evaluate and adopt new technology. |
| Critically analyse, interpret, and synthesise data from diverse sources to investigate complex problems and provide creative solutions that enhance and support organisational and strategic goals; | UC graduates are professional: Employ up-to-date and relevant knowledge and skills; communicate effectively; use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems; work collaboratively as part of a team, negotiate, and resolve conflict; display initiative and drive, and use their organisational skills to plan and manage their workload; take pride in their professional and personal integrity. UC graduates are global citizens: Think globally about issues in their profession; adopt an informed and balanced approach across professional and international boundaries; understand issues in their profession from the perspective of other cultures; communicate effectively in diverse cultural and social settings; make creative use of technology in their learning and professional lives; behave ethically and sustainably in their professional and personal lives. UC graduates are lifelong learners: Reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development; adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas; evaluate and adopt new technology. UC graduates are able to demonstrate Aboriginal and Torres Strait Islander ways of knowing, being and doing: Communicate and engage with Indigenous Australians in ethical and culturally respectful ways. |
| Design, implement and evaluate professional best practice approaches in data-driven programming, modelling, data management, data visualisation, and data mining tools as appropriate to the data, task and/or environment; |
UC graduates are professional: Employ up-to-date and relevant knowledge and skills; use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems; work collaboratively as part of a team, negotiate, and resolve conflict; display initiative and drive, and use their organisational skills to plan and manage their workload; take pride in their professional and personal integrity. UC graduates are global citizens: Think globally about issues in their profession; adopt an informed and balanced approach across professional and international boundaries; understand issues in their profession from the perspective of other cultures; make creative use of technology in their learning and professional lives; behave ethically and sustainably in their professional and personal lives. UC graduates are lifelong learners: Reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development; evaluate and adopt new technology. |
| Demonstrate advanced skills to professionally communicate complex theoretical and technical data science concepts, information, and ideas to a variety of audiences using appropriate media; |
UC graduates are professional: Employ up-to-date and relevant knowledge and skills; communicate effectively; use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems; work collaboratively as part of a team, negotiate, and resolve conflict; display initiative and drive, and use their organisational skills to plan and manage their workload; take pride in their professional and personal integrity. UC graduates are global citizens: Adopt an informed and balanced approach across professional and international boundaries; understand issues in their profession from the perspective of other cultures; communicate effectively in diverse cultural and social settings; make creative use of technology in their learning and professional lives; behave ethically and sustainably in their professional and personal lives. UC graduates are lifelong learners: Reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development; adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas; evaluate and adopt new technology. |
| Design, execute and critically evaluate a substantive research project that demonstrates an advanced and integrated understanding of collecting, processing, analysing and extracting meaning from complex data to investigate contemporary, real-world problems. | UC graduates are professional: Employ up-to-date and relevant knowledge and skills; communicate effectively; use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems; work collaboratively as part of a team, negotiate, and resolve conflict; display initiative and drive, and use their organisational skills to plan and manage their workload; take pride in their professional and personal integrity. UC graduates are global citizens: Think globally about issues in their profession; adopt an informed and balanced approach across professional and international boundaries; communicate effectively in diverse cultural and social settings; make creative use of technology in their learning and professional lives. UC graduates are lifelong learners: Reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development; adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas. UC graduates are able to demonstrate Aboriginal and Torres Strait Islander ways of knowing, being and doing: Communicate and engage with Indigenous Australians in ethical and culturally respectful ways. |
Awards
| Award | Official abbreviation |
|---|---|
| Master of Data Science | MDS |
| Master of Data Science in Sports Analytics | MDS SportAnalytics |
| Master of Data Science in Business Intelligence | MDS BusIntelligence |
| Master of Data Science in AI and Computational Modelling | MDS AICompModelling |
Enrolment data
2020 enrolments for this course by location. Please note that enrolment numbers are indicative only and in no way reflect individual class sizes.
| Location | Enrolments |
|---|---|
| UC - Canberra, Bruce | 76 |
Enquiries
| Student category | Contact details |
|---|---|
| Current and Commencing Students | In person, Student Centre Building 1 or Email Student.Centre@canberra.edu.au |
| Prospective International Students | Email international@canberra.edu.au or Phone +61 2 6201 5342 |
| Prospective Domestic Students | Email study@canberra.edu.au or Phone 1800 UNI CAN (1800 864 226) |
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