Our rankings
The University is ranked second in Australia for computer science & engineering in the 2021 Global Ranking of Academic Subjects.
Our graduates are ranked 1st in Australia and 4th globally for employability by the 2020 QS Graduate Employability Rankings.
In response to COVID-19, the University of Sydney has reviewed the availability of courses to be delivered remotely.
This course will be available for students to study remotely whilst the Australian border remains closed due to the COVID-19 global pandemic. Please note that some units of study that are not essential to completing the degree may not be available to be studied remotely.
About this course
The Master of Digital Health and Data Science provides specialised skills and knowledge in digital health and applied data science. Whether you’re looking to expand your digital science expertise to health data, or expand your skills in data science to specialise in digital health, this program will teach you new skills and provide practical experience to complement and build on your expertise.
With healthcare on the cusp of a major transformation through big data, machine learning, and computation, demand for applied data science qualifications and courses is increasing globally. The health sector needs people with the skills to develop, implement, evaluate, and manage data-driven technologies. In the private sector, companies are working directly on healthcare solutions, devices, and analytics platforms.
Recognising that the digital health workforce runs on the strength of multi-disciplinary teams, in this course you’ll learn from and work with engineers, IT specialists, data scientists, and health professionals on projects that come directly from industry and the healthcare sector.
Co-designed and co-taught by the School of Computer Science in the Faculty of Engineering, and Biomedical Informatics and Digital Health in the Faculty of Medicine and Health, all units have been specifically developed to provide you with advanced data science skills in the context of healthcare.
Students who are not immediately eligible for the MDHDS course can also start with the Graduate Certificate of Digital Health and Data Science (GCDHDS) and extend their study to the MDHDS. Students who wish to selectively study relevant topics can also choose from the GCDHDS in more focused study.
For academic requirements check the ‘Admission requirements’ section on this page.
You can apply online via the application portal. When you are ready to apply, select the ‘Apply’ button on this course page. Visit the How to apply page for other important information.
Semester 1 - 11 February of the commencing year
Semester 2 - 15 July of the commencing year
We strongly encourage applicants to apply as early as possible, offers are made on a rolling basis and places are limited. Separate scholarship deadlines apply - check the scholarships website for details.
Semester 1 (March) and Semester 2 (August)
You can apply online via the application portal. When you are ready to apply, select the ‘Apply’ button on this course page. Visit the How to apply page for other important information.
Semester 1 - 31 January of the commencing year
Semester 2 - 30 June of the commencing year
We strongly encourage international applicants to apply as early as possible to allow time for visa and travel arrangements. Separate scholarship deadlines may apply - check the scholarships website for details.
Semester 1 (March) and Semester 2 (August)
To be eligible for admission, an applicant is required to have:
*A cognate discipline includes Data Science, Computer Science, Mathematics, Statistics, Engineering, Physics, Economics, Finance, Health Sciences, Medical Sciences, or a related Health Profession or other disciplines that are deemed cognate by the Program Directors.
For qualifications awarded outside Australia, equivalencies and entry requirements are determined based on the country, institution and qualification.
As part of the embedded program, units completed under the Graduate Certificate in Digital Health and Data Science can be credited to the master’s degree.
For more information about the University’s credit policy, please see the Credit for Previous Studies page.
