Deakin’s Master of Data Analytics prepares students for professional employment across all sectors. The sheer volume and complexity of data already at the fingertips of businesses and research organisations gives rise to challenges that must be solved by tomorrow’s graduates. Become a data analytics specialist capable of using data to learn insights and support decision making.
Modern organisations are placing increasing emphasis on the use of data to inform day-to-day operations and long-term strategic decisions.
Throughout your studies you’ll learn to understand the various origins of data to be used for analysis, combined with methods to manage, organise and manipulate data within regulatory, ethical and security constraints. You’ll develop specialised skills in categorising and transferring raw data into meaningful information for the benefit of prediction and robust decision-making.
As a graduate, your knowledge, skills and competencies in modern data science and statistical analysis will be highly valued by employers seeking greater efficiencies and competitive advantage through data insights.
Units in the course may include assessment hurdle requirements.Read More
To complete the Master of Data Analytics, students must attain 16 credit points. Most units (think of units as ‘subjects’) are equal to 1 credit point. So that means in order to gain 16 credit points, you’ll need to study 16 units (AKA ‘subjects’) over your entire degree. Most students choose to study 4 units per trimester, and usually undertake two trimesters each year.
Students who are entering with a related academic/professional background may be eligible for credit transfer and recognition for up to 4 of the foundation units. Please contact your course advisor for more detailed information.
Year 1 - Trimester 1
Year 1 - Trimester 2
Year 2 - Trimester 1
Year 2 - Trimester 2
Four (4) credit points of project/thesis/placement units from the list below:
2 additional level 7 SIT/MIS course grouped elective units.
*Students undertaking this unit must have successfully completed STP710 Introduction to Work Placements (0 credit point)
Campuses by intake
Campus availability varies per trimester. This means that a course offered in Trimester 1 may not be offered in the same location for Trimester 2 or 3. Read more to learn where this course will be offered throughout the year.
Trimester 1 - March
- Start date: March
- Available at:
- Burwood (Melbourne)
- Cloud Campus
Trimester 2 - July
- Start date: July
- Available at:
- Burwood (Melbourne)
- Cloud Campus
Trimester 3 - November
- Start date: November
- Available at:
- Burwood (Melbourne)
- Cloud Campus
Additional course information
Course duration - additional information
Course duration may be affected by delays in completing course requirements, such as accessing or completing work placements.
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.
You will have an opportunity to undertake a placement as part of your course.
Deakin University offers admission to postgraduate courses through a number of Admission categories. In all categories of admission, selection is based primarily on academic merit as indicated by an applicant's previous academic record.
All applicants must meet the minimum English language requirements.
Entry will be based on performance in:
- a Bachelor degree or other qualification at a higher AQF level in any discipline OR
- other evidence of academic capability judged to be equivalent
For more information on the Admission Criteria and Selection (Higher Education Courses) Policy visit the Deakin Policy Library
Fees and scholarships
Learn more about fees and your options for paying.
The available fee places for this course are detailed above.
Tuition fees are determined by your enrolment:
- If you are offered a full fee paying place, your tuition fees are calculated based on your course.
- If you are offered a Commonwealth supported place, your tuition fees are calculated depending on the units you choose. Not all courses at Deakin have Commonwealth supported places available.
The 'Estimated tuition fee' is provided as a guide only based on a typical enrolment of students completing the first year of this course. The cost will vary depending on the units you choose, your study load, the length of your course and any approved Credit for Prior Learning.
* One year full-time study load is typically represented by eight credit points of study. Each unit you enrol in has a credit point value. The 'Estimated tuition fee' is calculated by adding together 8 credit points of a typical combination of units for your course.
You can find the credit point value of each unit under the Unit Description by searching for the unit in the Handbook.
Learn more about fees and available payment options.
A Deakin scholarship could help you pay for your course fees, living costs and study materials. If you've got something special to offer Deakin - or maybe you just need a bit of extra support - we've got a scholarship opportunity for you. Search or browse through our scholarships
Graduates of this course may find careers as data analysts, data scientists, analytics programmers, analytics managers, analytics consultants, business analysts, management advisors, management analysts, business advisors and strategists, marketing managers, market research analysts and marketing specialists.
Course learning outcomes
Deakin's graduate learning outcomes describe the knowledge and capabilities graduates can demonstrate at the completion of their course. These outcomes mean that regardless of the Deakin course you undertake, you can rest assured your degree will teach you the skills and professional attributes that employers value. They'll set you up to learn and work effectively in the future.
Deakin Graduate Learning Outcomes
Course Learning Outcomes
Discipline-specific knowledge and capabilities
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. Apply advanced knowledge and skills to decompose complex processes (from real world situations) to develop data analytics solutions for use in modern organisations across multiple industry sectors. Assess the role data analytics plays in the context of modern organisations and society in order to add value.
Communicate effectively in order to design, evaluate and respond to advances in data analytics approaches, technology, future trends and industry standards and utilise a range of verbal, graphical and written forms, customised for diverse audiences including specialist and non- specialist clients, colleagues and industry personnel.
Utilise a range of digital technologies and information sources to discover, select, analyse, synthesise, evaluate, critique and disseminate both technical and professional information.
Appraise complex information using critical and analytical thinking and judgement to identify problems, analyse user requirements and propose appropriate and innovative solutions.
Generate data solutions through the application of specialised theoretical constructs, expert skills and critical analysis to real-world, ill-defined problems to develop appropriate and innovative IT solutions.
Take personal, professional and social responsibility within changing national and international professional IT contexts to develop autonomy as researchers and evaluate own performance for continuing professional development. Work autonomously and responsibly to create solutions to new situations and actively apply knowledge of theoretical constructs and methodologies to make informed decisions.
Work independently and collaboratively towards achieving the outcomes of a group project, thereby demonstrating interpersonal skills including the ability to brainstorm, negotiate, resolve conflicts, manage difficult and awkward conversations, provide constructive feedback, and demonstrate the ability to function effectively in diverse professional, social and cultural contexts.
Engage in professional and ethical behaviour in the design, development and management of IT systems, in the global context, in collaboration with diverse communities and cultures.
Approved by Faculty Board 27 July 2017
How to apply
Apply direct to Deakin
Applications can be made directly to the University through the Applicant Portal if you are only applying for one course. For information on the application process and closing dates, see the how to apply web page. Please note that closing dates may vary for individual courses.Apply through Deakin
Need more information on how to apply?
For more information on the application process and closing dates, see the How to apply webpage. If you're still having problems, please contact us for assistance.
Register your interest to study at Deakin
Please complete the Register your interest form to receive further information about our direct application opportunities.
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Credit for prior learning
The University aims to provide students with as much credit as possible for approved prior study or informal learning which exceeds the normal entrance requirements for the course and is within the constraints of the course regulations. Students are required to complete a minimum of one-third of the course at Deakin University, or four credit points, whichever is the greater. In the case of certificates, including graduate certificates, a minimum of two credit points within the course must be completed at Deakin.
You can also refer to the Credit for Prior Learning System which outlines the credit that may be granted towards a Deakin University degree and how to apply for credit.
We invite industry speakers to our classrooms to show our students what they can do with the knowledge of data analysis and optimisation in real-life.
SENIOR LECTURER, SCHOOL OF INFORMATION TECHNOLOGY