Master of Data Analytics

2024 Deakin University Handbook

Year	2024 course information
Award granted	Master of Data Analytics
Deakin course code	S777
Faculty	Faculty of Science, Engineering and Built Environment
Campus	For students who commenced prior to 2019
Duration	1.5-2 years full-time or part-time equivalent depending on your entry point
CRICOS course code	089186E
Australian Qualifications Framework (AQF) recognition	The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 9
The final intake to this course version was in 2018. Students should contact a Student Adviser in Student Central for course and enrolment information. Further course structure information can be found in the Handbook archive.

Course sub-headings

Course overview

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 will 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.

Indicative student workload

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.

Career opportunities

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.

Participation requirements

Elective units may be selected that include compulsory placements, work-based training, community-based learning or collaborative research training arrangements.

Reasonable adjustments to participation and other course requirements will be made for students with a disability. More information available at Disability support services.

Mandatory student checks

Any unit which contains work integrated learning, a community placement or interaction with the community may require a police check, Working with Children Check or other check.

Alternative exits

Graduate Certificate of Data Analytics (S576)
Graduate Diploma of Data Science (S677)

Fees and charges

Fees and charges vary depending on the type of fee place you hold, your course, your commencement year, the units you choose to study and their study discipline, and your study load.

Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.

Use the Fee estimator to see course and unit fees applicable to your course and type of place. For further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods visit our Current students website.

Course rules

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 will 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.

The course comprises a total of 16 credit points, which must include the following:

Four (4) core foundation units (MIS770, MIS782, SIT772, SIT718)*
Four (4) core analytics units (MIS771, MIS772, SIT719, SIT720)
Four (4) ‘Data’ discipline specific units (SIT741, SIT742, SIT743, SIT744)
Four (4) credit points of core project/thesis/placement units from the list provided
Completion of STP050* Academic Integrity Module (0-credit-point compulsory unit)

* Core foundation units for students entering with a degree from a different discipline. 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.

Students are required to meet the University's academic progress and conduct requirements.

Work experience

You may have an opportunity to undertake a placement as part of your course. For more information, please visit deakin.edu.au/sebe/wil.

Other course information

Course duration

Course duration may be affected by delays in completing course requirements, such as accessing or completing work placements.

Further information

Student Central can help you with course planning, choosing the right units and explaining course rules and requirements.

Contact Student Central

Other learning experiences

You may choose to use one of your elective units to undertake an internship or participate in an overseas study tour to enhance your global awareness and experience.