Master of Science in Health Data Science

Overview

Until recently, if you’d looked into where our health data is collected by researchers across Australia, you would have encountered the usual suspects - hospitals, prescription records, aged-care facilities, and local GP clinics. 

But the future of big data is set to look very different when it comes to our health, because the rise of increasingly sophisticated personal devices such as iPhones and Fitbits means scientists can access information across all aspects of our daily lives. In addition, there’s a digital revolution occurring right across our health systems moving to make health data collection efficient and accessible for analysis.

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. There is also an option for a Graduate Diploma and Graduate Certificate. 

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.

The Master of Science, Graduate Diploma and Graduate Certificate in Health Data Science are Australasia’s first postgraduate programs in Health Data Science. 

The program is designed and run by the Centre for Big Data Research in Health. 

The Centre of Big Data Research in Health is a leading Australian and international hub for health research using big data. The aim of the centre is to maximise the productive use of all possible sources of health big data to enhance the health and well-being of Australians and the global community. 

At the Centre of Big Data Research in Health, its interdisciplinary team of staff have world-leading expertise in managing, manipulating, analysing and visualising health big data.

Why study a Master of Science in Health Data Science? 

  • Experience the entire Health Data Science pipeline, taught using real-world health data problems 
  • Opportunity to upskill in an emerging field with growing demand in industry. 
  • Glassdoor ranked “Data Scientist” consistently as the #1 top job in the US 2016-2019
  • "Data Scientist: The Sexiest Job of the 21st Century" 
  • Workplace, dissertation project or internship opportunities as part of the degree
  • Taught by world-leading experts in the field 
  • Be part of a vibrant community of researchers, educators and PhD students

 

“The Health Data Science programs are designed for those new to Health Data Science and those already working in the field looking to up-skill.

Whether  you are a statistician who wants to  build on your current skills with exposure to a field where you can make an impact; a clinician or nurse who wants to expand your capabilities  and improve the quality of care received by your patients; or a keen programmer looking to convert your “on-the-job” experience into a formal qualification, our programs welcome students from a wide range of backgrounds.”

-    Andrew Blance, Program Director Health Data Science, Centre for Big Data Research in Health 

 

“We sit at a key point in history, where big data are poised to become a dominant driver in what happens in health and healthcare. We have designed our programs in response to a significant and growing gap in the global health workforce: skilled data scientists who understand the context of health and can apply data analytics to drive health improvement.

The Health Data Science programs aim to equip graduates with the essential cognitive, analytical and communication skills needed to make sense of health big data.

How we make use of this data and transform it into action to better support clinical care, inform health policy and improve population health has never been more important than now.”

-    Professor Louisa Jorm, Director, Centre for Big Data Research in Health

 

Where can a Master of Science in Health Data Science take me? 

There is growing demand within the public and private health sector both in Australia and globally for professionals with specialised interdisciplinary skills in Health Data Science.

A Health Data Scientist can function at any stage along the Health Data Science pipeline.  

From designing and leading research studies or evaluations, conducting complex analyses or managing teams of data analysts, through to advising health policy makers on the outcomes of studies or analysis findings, a Health Data Scientist has the breadth of skills for a number of different jobs in the arena of health big data.

A Master of Science in Health Data Science can lead you to a career in:

  • Government departments of health (national, state or local), 
  • Hospitals
  • Universities and research institutes
  • Pharmaceutical companies
  • Health insurance companies 
  • Private data analytics consultancies.

 

image - Where can a Master of Science in Health Data Science take me?

Learn more:

Am I eligible?

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)

 

Note: 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

Admissions for our Term 1, 2020 and Term 3 are now open. 

The deadline to apply for international students are 31 January 2020 for Term 1 & 28 August 2020 for Term 3.

The deadline to apply for domestic students are 7 February 2020 for Term 1 & 4 September 2020 for Term 3.

Allow at least 3 weeks processing time for your application. To ensure your place in the program, it is recommended you apply early and well before the enrolment deadline. Please refer to the programs in the UNSW Handbook for entry requirements.

  1. APPLY ONLINE at UNSW Apply Online
  • Register with Apply Online with a valid email address
  • Provide evidence of previous education: certified copy of full official transcript of your academic record in English for all tertiary study undertaken
  • Provide evidence of English language requirement (if applicable): for more information visit here
  • Provide your Curriculum Vitae and Employer-provided statement of service (if applicable)
  1. TRACK APPLICATION at UNSW Apply Online
  • Successful applicants will be provided a Letter of Offer by email
  1. ACCEPT YOUR OFFER at Getting Started
  • Follow the instructions in the Letter of Offer and get started accepting your offer
  1. ENROL IN COURSES at Getting Started
  • Follow the prompts in the getting started website to enrol in courses online

 

Tuition fees
For information regarding UNSW Medicine tuition and other student fees, please refer to fees.

Financial assistance for Domestic students
FEE-HELP is an Australian Government loan scheme that assists eligible full fee-paying students to pay all or part of their tuition fees. Please refer to fee-help for more information.
 

About the UNSW Health Data Science program | Degree at a glance

Master of Science in Health Data Science

  • Course code: 9372 (72 units of credit)
  • Award type: Masters
  • 1.7 years full time or 3 years part – time 
  • Options for a Graduate Certificate 7372 (24 Units of Credit) and Graduate Diploma 5372 (48 Units of Credit).
  • On Campus or Fully Online

 

How is the program delivered?
You can view detailed information about coursework and subjects in the UNSW handbook

For non HDAT courses, please visit the respective Faculty and School pages for course outline.

Course Code Course Name Course Convenor(s) Term Offering Course Outline
HDAT9100  Context of Health Data Science Dr Amy Gibson T1 HDAT9100 Course Outline
HDAT9200 Statistical Foundations for Health Data Science Andrew Blance T1 & T3 HDAT9200 Course Outline
HDAT9300 Computing for Health Data Science Andrew Blance T1  
HDAT9400 Management and Curation of Health Data Sanja Lujic T2 & T3 HDAT9400 Course Outline
HDAT9500 Machine Learning and Data Mining Dr Oscar Perez Concha T2 & T3 HDAT9500 Course Outline
HDAT9600 Statistical Modelling 1 Andrew Blance T2 HDAT9600 Course Outline
HDAT9700 Statistical Modelling 2

Dr Mark Hanly

Dr Maarit Laaksonen

T3 HDAT9700 Course Outline
HDAT9800 Visualisation and Communication of Health Data  Dr James Farrow T2 HDAT9800 Course Outline

HDAT9900

HDAT9901

HDAT9902

Research Dissertation Dr Amy Gibson T1, T2, T3  
HDAT9910 Research Capstone Andrew Blance T1, T2, T3