Health Data Science - 7372

Program Summary

Faculty: Faculty of Medicine

Contact: MSc Health Data Science

Campus: Sydney

Career: Postgraduate

Typical Duration: 0.5 Years  

Typical UOC Per Semester: 24

Min UOC Per Semester: 6

Max UOC Per Semester: 24

Min UOC For Award: 24


Graduate Certificate in Health Data Science

View program information for previous years

Program Description

Health Data Science 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. Health Data Science is an emergent discipline, arising at the intersection of (bio)statistics, computer science, and health. The Graduate Certificate in Health Data Science (Grad Cert Health Data Science) covers the first part of the Health Data Science pipeline concerned with comprehension of health context, statistical foundations, principles of programming, and data wrangling and management.

The 24 UoC program can be completed in 6 months full-time or part-time equivalent. The initial offering in Semester 1, 2018 will be open to internal (face-to-face, on-campus) students only.

Program Objectives and Graduate Attributes

Grad Cert Health Data Science graduates will be well suited to an identified area of workforce demand, in both public and private health sectors. High-achieving graduates will have potential for consideration into entry to the Graduate Diploma in Health Data Science program 5372. The program is designed to appeal to both those new to Health Data Science and those already working in the field looking to up-skill. The Grad Cert Health Data Science is appropriate for both an Australian and international audience. Potential students from any undergraduate background and/or who possess relevant work experience will be considered for admission.

Program Learning Outcomes

1. Advanced disciplinary knowledge and practice
Graduates will be able to apply foundation Health Data Science principles to novel contexts.

2. Enquiry-based learning
Graduates will be able to apply enquiry-based learning and ways of thinking to Health Data Science contexts.

3. Cognitive skills and critical thinking
Graduates will be able to apply Statistical Thinking to synthesise and critically evaluate foundation Health Data Science concepts.

4. Communication, adaptive and interactional skills
Graduates will be able to communicate foundational Health Data Science principles to a range of audiences, in a variety of formats.

5. Global outlook
Graduates will be able to demonstrate an awareness of a global perspective for the potential of Health Data Science to positively impact health at both individual and community levels.

Program Structure

The 24 UoC coursework program is fully articulated with options for further study at Graduate Diploma and Master of Science.

Students must take 24 UoC of the following core courses:

Academic Rules

Students with at least a "Pass" in the core courses can be considered for entry into the Graduate Diploma in Health Data Science 5372 program.


For information regarding fees for UNSW programs, please refer to the following website:  UNSW Fee Website.

Entry Requirements

The entry criteria are:

- an undergraduate degree in a cognate discipline
- an undergraduate degree in a non-cognate discipline at honours level
- an undergraduate degree in a non-cognate discipline and minimum 1 year full-time equivalent of relevant work experience


- minimum 3 year full-time equivalent of relevant work experience

Cognate discipline is defined as a degree in one of the following disciplines:
- a science allied with medicine, including
biomedical/ biological science
public health
veterinary science
mathematical sciences
computer science
(health) economics
data science
other (case-by-case basis)

Relevant experience is defined as:
- any (professional) position involving data acquisition, management or handling (e.g. database manager)


any (professional) position involving analytics (e.g. data analyst)


- tertiary-level training, demonstrating capability in a cognate discipline
- exhibits potential to pursue postgraduate (level 8) studies

Evidence requirements will be a CV and an employer provided statement of service in relation to professional experience.

Recognition of Prior Learning

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. Credit (advance standing) is available for additional RPL beyond that acknowledged for program entry. Both formal and non-formal learning is considered. Recognition of formal learning is assessed for equivalence to an entire (HDAT) course, on a case-by-case basis. Credit granted for formal learning will yield specified credit for the equivalent 6 UoC course. Recognition of non-formal learning will result from micro-credentialing and awarding of Badges. Reduction in the total volume of learning due to advance standing is limited to a maximum of 12 UoC.
[an error occurred while processing this directive]