Overview

Health Data Science (HDS) is the science and art of generating data-driven solutions through comprehension of complex real-world health problems, employing critical thinking and analytics to derive knowledge from big data. HDS is an emergent discipline, arising at the intersection of biostatistics, computer science and health. The Master of Science (Health Data Science) covers the entire pipeline from comprehension of complex health issues, through data wrangling and management, machine learning and data mining, data analytics, data modelling and communication including data visualisation. The degree will appeal to you whether you are new to the field or already working in the industry and keen to develop your knowledge and skills. This degree is appropriate for Australian and international students.

Program Code

9372

CRICOS Code

096225M

Total units of credit (UOC)

72

Campus

Kensington

Indicative Enrolments

21

Why choose this degree?

Graduates of this degree will be well suited to an identified area of workforce demand, in both public and private health sectors.

Who should choose this degree?

Industry professionals and health care graduates choose this degree so they can explore the possibility of health solutions through analysing data.

Degree Structure

Degree Handbook

Career opportunities

  • Health data management
  • Health data analytics
  • Health research

Entry requirements

The entry criteria are:

an undergraduate degree in a cognate discipline an undergraduate degree in a non-cognate discipline at honours level *successful completion of Graduate Diploma in Health Data Science 5372 program or

*qualifications equivalent to or higher than Graduate Diploma in Health Data Science 5372 program on a case-by-case basis Cognate discipline is defined as a degree in one of the following disciplines:

  • a science allied with medicine, including

medicine nursing dentistry physiotherapy optometry biomedical/ biological science pharmacy public health veterinary science biology biochemistry statistics mathematical sciences computer science psychology (health) economics data science other (case-by-case basis) Recognition of prior learning (RPL) is awarded in accordance with UNSW 'Recognition of Prior Learning (Coursework Programs) Policy' and 'Recognition of Prior Learning Procedure' for both program admission and credit.

Criteria for RPL for admission is detailed in the program entry requirements.

How to apply

Applications must be submitted through our Apply Online portal. We encourage you to submit your completed application as early as possible to ensure it will be processed in time for your preferred term. Some high-demand programs and Faculties with limited places may have an earlier application deadline or commencement date. Find out more.

Apply Now
Back to listing