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La Trobe University

  • 24% international / 76% domestic

Master of Data Science

  • Masters (Coursework)

The two-year Master of Data Science will prepare you for a contemporary and rewarding career interpreting and making use of messy data.

Key details

Degree Type
Masters (Coursework)
Duration
2 - 4 years full-time
Course Code
SMDS, 092396B
Study Mode
In person

About this course

The two-year Master of Data Science will prepare you for a contemporary and rewarding career interpreting and making use of messy data. Whether you're looking for a commercial career or you want to help solve society's most important challenges, this degree will give you a unique combination of technical skills and real-world application. It will enable you to traverse any industry, any issue, any geography. The course has been developed in partnership with industry and researchers, and is delivered by an academic team that is shaping practice in Victoria and internationally. You can choose to major in Bioinformatics, Big Data and Cloud Computing or Analytical Science. You can also choose electives studies in Business Analytics to extend your skills and experience. Each major includes a set of core advanced subjects from computer science and mathematics/statistics disciplines and a number of specialised advanced subjects including big data high-performance programming, computational intelligence for analytics, cloud systems development, analysis of repeated measures data, meta-analysis, and bioinformatics technologies. The qualification awarded on graduation is recognised in the Australian Qualifications Framework (AQF) as Level 9. The course requires the completion of 240 credit points over two years of full-time or equivalent part-time study with a minimum of 120 credit points completed at fifth year level.

Entry requirements

IT and engineering courses
Level of Study
Bachelor

Study locations

Bundoora

Graduate outcomes

Graduate satisfaction and employment outcomes for Computing & Information Systems courses at La Trobe University.
80%
Overall satisfaction
77.6%
Skill scale
63.6%
Teaching scale