Master's Degree Computer Science Full Time

Master of Data Science

at University of Melbourne · Melbourne, Victoria

CRICOS course code

092791B

CRICOS provider code

00116K

This course is registered on the Commonwealth Register of Institutions and Courses for Overseas Students. Verify it yourself at cricos.education.gov.au before paying any fee.

Duration

2 years

Tuition (whole course)

A$121,767 total

Per year

A$60,884/yr

Intake

Semester 1 (Feb/Mar), Semester 2 (Jul)

About this program

The Master of Data Science at the University of Melbourne is a two-year postgraduate programme designed to equip students with advanced analytical, statistical, and computational skills. The course integrates core elements of computer science and statistics, preparing graduates to manage, analyse, and extract insights from complex data. Students build expertise in programming, machine learning, big data technologies, data visualisation, and predictive modelling.

This master's programme is structured around semesters, typically comprising a combination of core and elective units of study, each allocated credit points towards the degree. Students may also undertake a capstone project or research thesis, offering the opportunity to apply their knowledge to real-world data science problems, often in partnership with industry, research centres, or government agencies in the vibrant Melbourne technology and innovation ecosystem.

Throughout the course, students gain practical experience with contemporary data science tools, develop critical problem-solving skills, and deepen their understanding of ethical, legal, and social considerations in data use. Work-integrated learning opportunities, such as internships or industry placements, may be available to build professional experience and graduate employability.

The programme is ideal for graduates with a background in computing, mathematics, engineering, or a related field, who wish to pursue data-driven roles across a range of industries. International applicants must provide evidence of English proficiency in line with the University’s requirements. Students may be eligible to work up to 48 hours per fortnight during study and can explore post-study work opportunities in Australia through the Temporary Graduate visa (subclass 485). Please confirm all programme details and entry requirements on the official University of Melbourne page.

Entry requirements

English: International applicants must evidence English proficiency. IELTS Academic 6.0–6.5 overall is the common undergraduate and coursework-postgraduate standard, rising to 7.0–7.5 for teaching, nursing, medicine, law and social work. TOEFL iBT, PTE Academic, Cambridge C1 Advanced and the university’s own English programmes are accepted as equivalents; the Department of Home Affairs sets a separate English threshold for the Student visa itself.

International students: Registered on CRICOS for international students. A Confirmation of Enrolment (CoE) for this course supports a Student visa (subclass 500) application; Overseas Student Health Cover is required for the full duration.

Career outcomes

Data Scientist in technology, finance, healthcare, and consulting organisations
Data Analyst for government agencies and research institutions
Machine Learning Engineer at startups or established businesses
Business Intelligence Specialist in corporate or public sectors
Big Data Engineer within Australia's digital and analytics industries
Advanced research roles or doctoral study

Frequently asked questions

How long is the Master of Data Science at University of Melbourne?

It typically takes 2 years, with intakes in Semester 1 (Feb/Mar), Semester 2 (Jul).

How much is the tuition?

Tuition is around A$121,767 total. Fees change yearly — confirm with an advisor.

What are the career outcomes?

Data Scientist in technology, finance, healthcare, and consulting organisationsData Analyst for government agencies and research institutionsMachine Learning Engineer at startups or established businessesBusiness Intelligence Specialist in corporate or public sectorsBig Data Engi...

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