Master of Data Science

La Trobe University

Type of institution: University/Higher Education Institution
Level: Postgraduate
CRICOS: 00115M

Are you ready to take on big data?Now, more than ever, the world is demanding clever solutions to society's evolving problems.Employers from a range of sectors—from science to finance—are searching for intelligent minds who understand data science and can also apply their knowledge of their industries. However, there simply aren't enough people to fill these roles.*To help fill this gap, we've carefully designed our Master of Data Science to give you a solid foundation in computer science, statistics and applied data analysis. Developed in partnership with industry leaders, it'll give you the opportunity to specialise in big data and cloud computing, analytical science, or bioinformatics—and also gain practical experience through a research project or an intensive industry placement with organisations like Australian Institute of Sport, Telstra or the Peter MacCallum Cancer Centre. La Trobe also has industry partnerships with Optus, Cisco and Pivot Maritime.


Students must complete 240 credit points over two years of full-time or equivalent part-time study, including a minimum of 120 credit points at fifth year level.


  • Bioinformatics
  • Big data and cloud computing
  • Analytical science

Standard entry requirements

Australian Bachelor degree (or equivalent) in computer science, information technology, computer engineering, or science with a major in mathematics or statistics. NB: Meeting minimum prerequisites does not guarantee an offer of a place. Entry into all La Trobe courses is based on competitive selection and there may be limited places available.

Study information

CampusFeesMid year intakeAttendance
Melbourne International: $73,600 No
  • Full-time : 2 years

Further information

This course requires prior knowledge in cognate areas of either Computer Science, IT, and/or Mathematics and Statistics. The course starts with a semester of core fundamental subjects designed to address knowledge gaps in the required cognate skills. E.g. students who have completed a Computer Science degree will need to choose fundamental subjects in Statistics and vice versa.

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