Master of Science in Health Data Science (Extension)
Domestic
International
Learn to unlock the data and deep dive into research to solve complex global health issues.
Faculty
Faculty of Medicine and Health
Delivery Mode
Face-to-face (includes blended), Online
Award
Master of Science (Extension)
Commencing Terms
Term 1, Term 3
Duration (Full Time)
2 Years (F/T); 4 Years (P/T)
- Overview
- Entry requirements
- What will I study?
- Future careers
- How to apply
- Fees & Scholarships
Overview
The Master of Science in Health Data Science will prepare you to find the right data, unlock hidden insights and use this information to better support clinical care, inform health policy and improve population health.
The two-year Master of Science in Health Data Science (Extension) builds upon this, offering an opportunity to dive deeper into different aspects and applications of Health Data Science through a research dissertation or a work placement. This research can involve analysing big data to solve health issues or involve the development of health-related data driven application. You’ll be perfectly positioned to pursue a PhD in Health Data Science to further advance your career.
Key features
- Industry relevant degree
We designed this program 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. In this program, you’ll be exposed to real-world problems and learn the latest analytical methodologies to derive solutions.
- Suited to a wide range of backgrounds
This degree is suitable for students who are starting out in the field and those already working within it who want to upskill. Whether you’re a statistician who wants to build on your current skills, a clinician or nurse who wants to 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, this program welcomes students from a wide range of backgrounds.
- Flexible delivery
This degree can be completed full-time or part-time, on-campus or fully online. Content is delivered through a combination of online readings, expert guest lectures and practical hands-on tutorials. Lectures are followed by exercises, which reinforce the learning and programming skills covered in the tutorials.
Why study this degree at UNSW?
Study the first postgraduate degree in health data science
Our master’s degree, graduate diploma and graduate certificate in health data science are pioneering programs that examine data-driven solutions to complex health problems. At UNSW, we’re leading this new approach to healthcare.
Learn within a world-leading research and teaching institute
This degree is delivered by the Centre for Big Data Research in Health (CBDRH) – the leading Australian and international hub for health research using big data. The CBDRH brings together an interdisciplinary team of staff, who have world-leading expertise in managing, manipulating, analysing and visualising health big data. Using large-scale electronic data than spans the biomedical, clinical and health services domains, the CBDRH is transforming knowledge from data into practical applications within health.
Connect with staff and students in a dynamic learning environment
In some courses, a flipped classroom approach is used, where you’ll learn theory from short online videos and use face-to-face or online sessions to apply knowledge, practice skills and engage in peer-to-peer learning. A major feature of our student-centric learning experience is the online community, where you can interact with your peers and instructors from diverse backgrounds and workplaces.
Program Code
9373
CRICOS Code
110655A
Campus
Kensington
Total Units of Credit (UOC)
96
Want to see more from UNSW Medicine and Health?
Entry requirements
For entry into this degree, you must have one of the following:
- an undergraduate degree in a cognate discipline
- an undergraduate degree in a non-cognate discipline at honours level
- successful completion of the Graduate Diploma in Health Data Science (5372)
- qualifications equivalent to or higher than the Graduate Diploma in Health Data Science (5372) on a case-by-case basis.
Cognate disciplines
- 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)
English language requirements
You may be asked to provide evidence of your English proficiency to study at UNSW depending on your educational background and citizenship. English language skills are vitally important for coping with lectures, tutorials, assignments and examinations - this is why UNSW requires a minimum English language competency for enrolment.
If you’re completing an Australian Year 12 qualification (e.g. NSW HSC or equivalent), you do not need to provide anything extra to prove your proficiency. Your qualification will be used as evidence of your English proficiency.
If you do need to provide evidence of your English proficiency, this will be indicated in your application. You can prove this by providing evidence that you meet one or more of the following criteria:
- English language tests and university English courses
- Prior study in the medium of English
- Other qualifications
If you need to improve your English skills before you start your degree, UNSW College’s Academic English Programs are for you. The programs are suitable for various English levels and help you prepare for university studies and life in Australia.
For entry into this degree, you must have one of the following:
- an undergraduate degree in a cognate discipline
- an undergraduate degree in a non-cognate discipline at honours level
- successful completion of the Graduate Diploma in Health Data Science (5372)
- qualifications equivalent to or higher than the Graduate Diploma in Health Data Science (5372) on a case-by-case basis.
Cognate disciplines
- 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)
English language requirements
You may be asked to provide evidence of your English proficiency to study at UNSW depending on whether you are from an English-speaking background or non-English speaking background. English language skills are vitally important for coping with lectures, tutorials, assignments and examinations - this is why UNSW requires a minimum English language competency for enrolment.
If English is not your first language, you’ll need to provide proof of your English proficiency before you can be given an offer to study at UNSW. You can do this by providing evidence that you meet one or more of the following criteria:
- English language tests and university English courses
- Prior study in the medium of English
- Other qualifications
If you need to improve your English skills before you start your degree, UNSW College’s Academic English Programs are for you. The programs are suitable for various English levels and help you prepare for university studies and life in Australia.
Check the specific English language requirements for this program
Program structure
From the context of health and data curation through to analytics, computation and communication, this degree will guide you through the entire health data science pipeline.
Health Data Science Pipeline
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- Health Delivery Systems
- Data Sources
- Evidence-Based Medicine
- Health Outcomes
- Health Equity and Genes
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- Data Quality
- Wrangling
- Data Linkage
- File Management /Storage
- IT Security
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- Pattern Analysis
- Pre-Processing
- Outlier Detection
- Prediction
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- Algorithms
- Models
- Decision Making
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- Collaborative Coding
- Visualisation
- Written and Oral Presentation
Full program structure
The Master of Science in Health Data Science (Extension) can be completed in two years of full-time study or four years part-time. The program is made up of 16 courses total, including:
- Eight core courses
- Four prescribed elective courses
- Additional electives which include a research project or work placement
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- Context of Health Data Science
- Statistical Foundations for Health Data Science
- Management and Curation of Health Data
- Health Data Analytics: Machine Learning I
- Health Data Analytics: Statistical Modelling I
- Health Data Analytics: Statistical Modelling II
- Visualisation and Communication of Health Data
- Principles of Programming or Computing for Health Data Science
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Students must complete 24 UOC (Units of Credit) of research courses.
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Electives are grouped into the following themes:
- Bioinformatics
- Health informatics
- Algorithms
- Data Management
- Web
- Statistical Theory
- Statistical Analytics
- Pharmaceutical
- Public Health
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The graduate certificate, graduate diploma and Master of Health Data Science provide an articulation pathway into the Master of Science in Health Data Science (Extension).
Future careers
The role of a health data scientist is dynamic and always evolving as their work spans across any of the multiple stages of the health data pipeline. From designing and leading research studies and analysing data, through to building machine learning processes to understand complex health issues, a health data scientist’s work draws on a multiplicity of skills.
Because it’s a profession in its early development stages, new roles and opportunities in this sector are being created all the time. The health data scientist may, for example, manage a team of data analysts to work out processes to gather data, assess how to model the data or devise ways to implement health policy change based on the outcomes of their studies and findings.
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. This degree could lead 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.
High-achieving students will also be well suited to further academic study, particularly at PhD level.
Our alumni
"We learnt industry-leading coding practices such as GitHub and Version Control and had regular assignments, which were useful as they were in a health context.”
Phillip Hungerford
Analytics Consultant
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.
Ready to start your application?
For most international students, applications are submitted via our Apply Online service. 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 with limited places, may have an earlier application deadline or may have an earlier commencement date. For more information visit our international applicant information page.
Ready to start your application?
Fees & Scholarships
2023 Indicative First Year Full Fee
$33,240*
2023 Indicative Full Fee to Complete Degree
$67,060*
Full Fees are the cost of the degree for students who do not receive a CSP place.
*Fees are subject to annual review by the University and may increase annually, with the new fees effective from the start of each calendar year. The indicative fees listed here are based on an estimated average and are for tuition only other fees and charges are not included. The amount you pay will vary depending on the calendar year to enrol, the courses you select and whether your study load is more or less than 1 Equivalent Full Time Student Load (8 courses per year). Indicative fees are a guide for comparison only based on current conditions and available data. You should not rely on indicative fees. More information on fees can be found at the UNSW fees website
Indicative fees to complete the program have been calculated based on a percentage increase for every year of the program. Fee increases are assessed annually and may exceed the indicative figures listed below.
2023 Indicative First Year Fee
$41,800*
2023 Indicative Fee to Complete Degree
$84,870*
*Fees are subject to annual review by the University and may increase annually, with the new fees effective from the start of each calendar year. The indicative fees listed here are based on an estimated average and are for tuition only other fees and charges are not included. The amount you pay will vary depending on the calendar year to enrol, the courses you select and whether your study load is more or less than 1 Equivalent Full Time Student Load (8 courses per year).
Indicative fees are a guide for comparison only based on current conditions and available data. You should not rely on indicative fees. More information on fees can be found at the UNSW fees website.
Indicative fees to complete the program have been calculated based on a percentage increase for every year of the program. Fee increases are assessed annually and may exceed the indicative figures listed here.
Indicative fees to complete the program include tuition plus an estimate of study-related costs of approximately $1,000 per year. To find out more about other costs, visit UNSW International.
Scholarships
At UNSW, we award over $83 million in scholarships each year. We pride ourselves on rewarding excellence and making university accessible to students from all walks of life. Whether you’re a domestic or international student, our range of scholarships, prizes and awards can support your journey.
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Top 20WorldwideQS World University Rankings, 2024.
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MostEmployable GraduatesAFR Top 100 Future leaders Award.
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LeadingInnovation#1 Australian uni attended by start-up founders.
I was able to improve my skills in data science and apply the knowledge to health-related areas.
