Top 150 worldwide for computer science
Top global growth in data careers
Get credit points for recognised prior learning
Why choose data science (global) at Deakin
Study the Master of Data Science (Global) to build advanced skills in data science, machine learning and artificial intelligence. Designed for information technology (IT) professionals, this degree helps you extend your knowledge and apply data in a range of contexts.
Delivered in partnership with Great Learning, the degree builds on prior postgraduate study and progresses to further study at Deakin. You will deepen your expertise in areas such as data analysis, machine learning, and applied analytics.
Through practical tasks and projects, you will learn how to prepare data, develop models, and generate insights to support informed decision-making across a range of industries.
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Structured pathway to a masters degree
Progress from a recognised program into a Deakin masters degree, building advanced data science expertise.
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Advance your expertise as a professional
Build on your IT or analytics background with advanced skills in data science, machine learning and artificial intelligence (AI).
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Study a high-growth discipline
Data science and AI are among the fastest-growing global fields, with strong demand for skilled professionals.
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Build skills employers value
Graduate with capability in data analysis, modelling and machine learning, aligned with demand across technology and business roles.
Connected to industry
Deakin’s strong industry connections help shape your learning. Build practical experience in real workplace contexts through work-integrated learning, mentoring and networking opportunities. Industry advisory boards also help shape our degrees, which means what you study is current, relevant and aligned to what your future employers need.
Deakin puts employability first
Career outcomes
Advance in your current role or expand your career opportunities with skills in data science, machine learning and AI. You could pursue roles spanning data and business analytics, consulting, management, strategy and marketing.
Data scientist
Analyse large and complex datasets to uncover insights, build predictive models and solve business problems. Apply statistical analysis, machine learning and programming skills to support data-driven decision-making.
- $125K
Typical annual salary in Australia
- 4.2/5
Job satisfaction
Data analyst
Collect, prepare and interpret data to identify trends and provide actionable insights. Work with stakeholders to help organisations make informed decisions using evidence-based analysis and reporting.
- $105K
Typical annual salary in Australia
- #11
Fastest-growing job globally
Other jobs
- Analytics programmer
- Analytics consultant
- Analytics manager
- Business analyst
- Market research analyst
- Marketing specialist
FAQs
The cost of studying at Deakin depends on your degree, units and study load – tuition fees are listed on degree pages under the fees and scholarships tab. Beyond tuition, you will need to budget for Overseas Student Health Cover (OSHC), accommodation, transport, groceries and textbooks. Find out more about the cost of living in Australia, use the Study Australia calculator to estimate living expenses and explore international scholarships which may help to reduce your tuition costs.
Deakin offers a range of merit-based scholarships that can reduce your postgraduate tuition fees by 20%, 25%, 50% or 100% for the duration of your degree. Eligibility varies by scholarship and the degree you choose, but you will automatically be considered for most scholarships when you apply to Deakin. Use the Find a scholarship tool and filter by 'citizenship' to see what is available to you, or explore Australia Awards scholarships if you are from an eligible country.
It depends on the degree and how you study. Graduate certificates typically take six months full time or one year part time. Graduate diplomas usually take one year full time and masters degrees typically take one to two years full time. Recognition of prior learning can reduce your study time. Check the degree page for full details.
Australia is widely regarded as one of the safest and most welcoming countries in the world for students, with strong legal protections, reliable public services and a multicultural community. In fact, Melbourne is ranked the #4 student city in the world! At Deakin, you will be part of a supportive community, with 24/7 help, dedicated campus security and practical tools to help you feel safe, confident and connected. Deakin’s SafeZone app also connects you directly to campus security and support services if you ever need help. Find out more about studying in Australia.
We value your experience and qualifications. That is why every new degree application at Deakin is assessed for recognition of prior learning (RPL). Through RPL, Deakin can assess your previous study and life experience and may award course credit that could reduce your study duration, as well as the cost of your study. Qualifications from universities and private tertiary institutions worldwide are considered, as is informal learning related to your degree. Use the RPL calculator to see how much credit you may be eligible for.
Deakin offers a wide range of support to help you settle in and succeed throughout your studies – we are ranked the #1 university in Melbourne for student support. You can access 1:1 study support, English language support, career planning help, disability services and free counselling, as well as financial assistance if you need it. On campus, the SafeZone app and 24/7 security services mean help is always within reach. You can explore the full range of support services for international students or start an online chat with a student ambassador before you arrive.
To enrol in a postgraduate degree at Deakin, many degrees require a minimum IELTS score of 6.0 (or equivalent). Some degrees require higher scores, so check the entry requirements tab on the degree page for details. You may also meet the requirement through recent secondary or university study completed in English, or by demonstrating five or more years of living and working in an English-speaking country. Eligibility is assessed on a case-by-case basis. If you do not yet meet the requirement, the Deakin University English Language Institute (DUELI) offers pathway programs to help develop your English reading, writing, listening and speaking skills. Completion of DUELI’s English for Academic Purposes can give you the minimum English language requirements for most Deakin degrees.
Deakin’s postgraduate degrees are designed to advance your career, whether you want to deepen expertise in your field, move into a specialist role or shift direction entirely. All our degrees are shaped by industry partners, so what you learn reflects what employers need now and into the future. We’re proud to be the #1 university in Melbourne for international student graduate employment. With flexible study options and financial support available, Deakin helps you gain the skills, recognition and confidence to reach your next professional goal.
*Deakin references data from a range of government, higher education and reputable media sources. Learn more about our achievements on our University rankings page, or explore our sources page for supporting references.
What will I study in the Master of Data Science (Global)?
This degree combines a pathway program with Deakin study, where you build core knowledge before progressing to advanced data science, machine learning and analytical techniques.
Advanced data science and applied analytics
Mathematics and modelling foundations
Build the mathematical and statistical knowledge that underpins data science and artificial intelligence (AI), supporting how models are developed and applied.
Machine learning and data techniques
Learn how to prepare, manage and analyse data, applying supervised and unsupervised learning methods to identify patterns and produce reliable results.
Applied data science and AI solutions
Develop skills across the full data process, from preparing and analysing data to optimisation and designing AI-based solutions for practical use.
Course structure
To complete the Master of Data Science (Global) students must pass 12 credit points.
Graduates of the Postgraduate Program in Artificial Intelligence and Machine Learning (PGPAIML) or Postgraduate Program in Data Science and Business Analytics (PGPDSBA) who have successfully completed Great Learning units equivalent to 6 credit points as recognised by Deakin; and will have met the minimum requirements for admission to Deakin, will be eligible for enrolment into the Deakin course with 6 credit points of Recognition of Prior Learning (RPL) and will be required to successfully complete 6 units with Deakin University in online mode in order to qualify for the Deakin Master of Data Science (Global) Award. i.e.
- 6 x Deakin units
- 6 x RPL
The Deakin component of the structure consists of all existing units which will be delivered online over a period of a year (3 x trimesters). Students will enrol part-time, undertaking 2 units (2 credit points) each trimester. Outlined below are the units.
Are you a current student? For course information that applies to the year you started your degree, visit the handbook.
All students are required to meet the University's academic progress and conduct requirements
Units
You are required to complete eight core units and four level 7 course elective units (these are essential units for this degree).
In your first trimester you must also complete a 0-credit point unit which is compulsory for all Deakin University degrees.
Recognition for prior learning (RPL) (based on Great Learning programs)
4 x level 7 course-grouped units
Deakin units
^ Recognition for prior learning (RPL) granted upon entry into the course
What to expect while studying
You can expect to participate in a range of teaching activities each week. This could include classes, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.
When can I start?
This course is only available to students via the Great Learning pathway. This course is not available to international students studying onshore in Australia. This course is offered part-time only.
Your course learning outcomes describe the knowledge, skills and capabilities you’ll develop and be able to demonstrate by the time you graduate. Built into your course through your units and assessments, they provide a clear picture of what you’ll be equipped to know, understand and do – preparing you to apply your learning with confidence beyond university.
| Course Learning Outcomes |
|---|
| Develop a broad, coherent knowledge of the analytics discipline, including: the origin and characteristics of data; the methods and approaches to dealing with data appropriately and securely; and how the use of analytics outcomes can be used to improve business, organisations or society. |
| Communicate in professional and other context to inform, explain and drive sustainable innovation through data science and to motivate and effect change by drawing upon advances in technology, future trends and industry standards, and by utilising a range of verbal, graphical and written methods, recognising the needs of diverse audiences including specialist and non-specialist clients, industry personnel and other stakeholders. |
| Identify, evaluate, select and use digital technologies, platforms, frameworks, and tools from the field of data science to generate, manage, process and share digital resources and justify digital tools selection to influence others. |
| Questions assumptions and seeks to uncover inconsistencies and ambiguities in information and judgements, critically evaluates their sources and rationales, to inform and justify decision making in the field of data science. |
| Apply expert, specialised cognitive, technical, and creative skills from data science to understand requirements and design, implement, operate, and evaluate solutions to complex real-world and ill-defined computing problems. |
| Apply reflective practice and work independently to apply knowledge and skills in a professional manner to complex situations and ongoing learning in the field of data science with adaptability, autonomy, responsibility, and personal and professional accountability for actions as a practitioner and a learner. |
| Work independently and collaboratively within multidisciplinary environments to achieve team goals, contributing advanced knowledge and skills from data science to advance the teams objectives, employing effective teamwork practices and principles to cultivate creative thinking, interpersonal adeptness, leadership skills, and handle challenging discussions, while excelling in diverse professional, social, and cultural scenarios. |
| Engage in professional and ethical behaviour in the field of data science, with appreciation for the global context, and openly and respectfully collaborate with diverse communities and cultures. |
- Award granted
- Master of Data Science (Global)
- Year
2027 course information
- Deakin code
- S773
- Australian Qualifications Framework (AQF) recognition
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9
Fees
Estimated tuition fee
For fee information please refer to Great Learning
Scholarships
Apply now
Apply through Great Learning
Applications can be made directly to Great Learning. (Note this link is for Great Learning applicants based in India. It is unavailable when accessing from Australia). For more information on the application process and closing dates, please email Great Learning or call +91 804 718 7565.
Recognition of prior learning
We value your previous study and experience. Recognition of prior learning enables you to get credit for what you've already achieved. When you apply, we'll consider your previous study and experience for recognition of prior learning.
Pathways
The Master of Data Science (Global) builds upon the postgraduate programs from Great Learning with units that extend students into the data science area. Units within the Deakin delivered content are independent of each other and provide coverage of the mathematical foundations that underpin data science, machine learning, engineering, and IT solutions that incorporate artificial intelligence, preparation of data, and analytics for real world projects.