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Health Informatics and Data Science● OpenMastersPreview

Master of Health Data Science

A multidisciplinary master’s programme blending biostatistics, computer science, and health to extract actionable insights from complex health data.

Best for:Best for professionals and graduates with backgrounds in health sciences, computer science, or related fields seeking to specialise in extracting insights from health data using advanced analytics and machine learning.

UNSW Sydney · Kensington, Australia
More professors at UNSW Sydney
health data analyticsmachine learning in healthcaredata visualisation for healthbig data in biostatisticsdata modelling and healthdata-driven health solutions
This is a masters position — not a PhD studentship.
Deadline
—
Funding
—
Start date
flexible (depends on intake)
Full-time
Location
Kensington
Australia

Overview

The Master of Health Data Science at UNSW Sydney is designed to equip students with the skills to transform raw health data into meaningful solutions. This interdisciplinary programme integrates biostatistics, computer science, and health sciences to cover the entire data pipeline—from problem comprehension and data wrangling to machine learning, analytics, modelling, and visualisation. Ideal for both newcomers to the field and professionals seeking to upskill, the degree caters to a global audience, including international students. It emphasises critical thinking and practical application, preparing graduates to address real-world health challenges through data-driven approaches.

health data sciencebiostatisticscomputer science in healthcaredata analyticsmachine learning applicationshealth data visualisationdata-driven healthcareinterdisciplinary health data

What you'll do

  • Develop and apply advanced data analytics techniques to solve complex health problems.
  • Learn to manage, clean, and integrate large-scale health datasets using cutting-edge tools.
  • Apply machine learning and data mining methods to derive actionable insights from health data.
  • Create visualisations and reports to communicate findings effectively to stakeholders.
  • Engage in hands-on projects that bridge the gap between data science and healthcare applications.
  • Collaborate with interdisciplinary teams to address real-world health challenges.

Requirements

Degree offered: Master of Health Data Science

Language: English proficiency (if applicable, as per UNSW admission requirements)

Instruction: English

Nice to have
Background in health sciences, computer science, statistics, or related fieldsFamiliarity with data analysis tools (e.g., Python, R, SQL)Experience with machine learning or data mining techniquesInterest in applying data science to healthcare contexts
Eligibility
  • Open to Australian and international students
  • No specific prior degree required, but relevant background is preferred

Funding & terms

Type
Unknown
Amount
—
Duration
—
Programme
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Programme and admissions

Admissions not verified

A catalogue listing does not mean applications are open or funding is guaranteed. Check the source for your intake.

Intake
Not confirmed by the source
Duration
Not confirmed by the source
Teaching language
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Taught / research mode
Not confirmed by the source
Study mode
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Campus
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Prerequisites
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Application instructions
Not confirmed by the source
Tuition
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Funding
Not confirmed by the source

How to apply

Deadline: unknown

Applicants must apply through the official UNSW postgraduate application portal. The process involves submitting academic transcripts, a personal statement, and any relevant professional documentation. International students may need to provide additional documentation such as proof of English proficiency.

Documents required
  • Academic transcripts
  • Personal statement or statement of purpose
  • Curriculum Vitae (CV)
  • Proof of English proficiency (if applicable)
  • Passport or identification documents (for international students)
↗Check programme and admissions

Contact

Lab
UNSW Medicine
UNSW Sydney
Australia
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Check admissions, intake and funding with the official source; a listing does not mean applications are open.