RMIT is committed to providing students with an education that strongly links formal learning with workplace experience.

You will learn through a broad mix of study modes including lectures, tutorials, practical classes, project work and seminars using face-to-face, online and other flexible delivery mechanisms.

The degree has substantial links with the data science profession and related areas of business and industry, both in Australia and internationally.

The subjects are taught by academics with strong research backgrounds and links to industry, as well as sessional teachers, guest lecturers and leaders working in industry.

Employers and industry professionals with data science expertise are members of our Industry Advisory Committee and have contributed to the initial development and ongoing improvement of the degree. Their involvement ensures that the degree remains relevant to your needs as a graduate and the needs of employers.

Academics teaching in this course are also involved in RMIT’s Centre for Information Discovery and Data Analytics, a research hub for advanced data science projects, supporting researchers and helping Victorian and Australian businesses compete globally. This Centre applies text, user and data research to industry-driven projects that solve problems and provide efficiencies in key areas including smart cities, health, logistics, the environment, and transportation. With its industry links and data focus, the centre is an excellent resource for master students to gain networking access to researchers in the field and project partners.

RMIT also collaborates with the Melbourne Data Science Meetup, one of the largest of its kind in the world, which provides clear pathways into the data science community on both a social and professional level. In fact, teams of RMIT students were runner-up in the Melbourne Datathon in both 2018 and 2019 and were subsequently hired by the ANZ Bank and other corporates.

This degree is delivered on-campus. You will learn through a broad mix of study modes including lectures, tutorials, practical classes, project work and seminars.

Full-time study of this degree typically includes four nights per week, totalling around 16 hours of contact per week, and a further 24-30 hours of private study. Part-time enrolment enables local students to manage a lighter load.

The knowledge and skills you will acquire throughout this degree and how they can be applied in your career are described in the learning outcomes.

The Master of Data Science's first year develops a solid foundation in computer science and statistics - core skills necessary for every data scientist in their professional work.

Students with an undergraduate background in either of these areas may gain some advanced standing, whereas students from other disciplines will first complete the introductory courses needed to prepare them for studying the advanced core courses and electives in the second year.

The second year includes a major project, which can be working on an industry or research problem while based on campus, or off-campus as an internship working as a data scientist with an industry partner.

The real-world focus of this degree provides an excellent networking environment that can lead to internship and industry-led project opportunities.

Building familiarity with programming and statistical techniques and tools, you’ll develop the technical and analytical skills essential for managing large data sets and making sense of them.

Faced with complex collections of data, you’ll be able to solve problems through in-depth analysis and evaluation.

To prepare you further for your data science career, whether in industry or research, you’ll also undertake case studies with input from industry-based data scientists, looking at the legal, ethical and policy issues that arise.