Master of Digital Health and Data Science

Please check the current students website (Find a unit of study) for up-to-date information on units of study including availability.

 
For more information on degree program requirements visit CUSP.

Unit outlines will be available through Find a unit outline.  

Unit of study Credit points A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition Session

Digital Health and Data Science

Master of Digital Health and Data Science

Students complete 48 credit points, comprising:
(i) 24 credit points of Core units of study;
(ii) 6 credit points of Data Science Elective units of study;
(iii) 6 credit points of Digital Health Elective units of study;
(iv) 12 credit points of Capstone Project units of study;

Graduate Certificate in Digital Health and Data Science

Students complete 24 credit points, comprising:
(i) 6 credit points of Data Science Selective units of study;
(ii) 6 credit points of Digital Health Selective units of study;
(iv) 6 credit points of Data Science Elective units of study or 6 credit points of Data Science Selective units of study; and
(iv) 6 credit points of Digital Health Elective units of study or 6 credit points of Digital Health Selective units of study.

Core Units

HTIN5006
Foundations of Healthcare Data Science
6      Semester 1
HTIN5005
Applied Healthcare Data Science
6      Semester 2
HSBH5003
e-Health for Health Professionals
6   

Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
BIDH5000
Implementation Science in Digital Health
6    A Assumed basic knowledge of health, health care and associated systems are required. Students who have not completed an undergraduate or postgraduate degree in a health profession will be asked to complete the Open Learning Environment module "Preparation for learning in the Hospital Environment', which is openly available to all University of Sydney students via Canvas. Please check the Canvas site for this unit for any information on further recommended resources


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 2

Selective units of study (Graduate Certificate)

For Graduate Certificate, Selective units are the same as the Core units offered in MDHDS
Data Science Selectives
HTIN5006
Foundations of Healthcare Data Science
6      Semester 1
HTIN5005
Applied Healthcare Data Science
6      Semester 2
Digital Health Selectives
HSBH5003
e-Health for Health Professionals
6   

Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
BIDH5000
Implementation Science in Digital Health
6    A Assumed basic knowledge of health, health care and associated systems are required. Students who have not completed an undergraduate or postgraduate degree in a health profession will be asked to complete the Open Learning Environment module "Preparation for learning in the Hospital Environment', which is openly available to all University of Sydney students via Canvas. Please check the Canvas site for this unit for any information on further recommended resources


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 2

Elective units of study

Data Science Electives
INFO5306
Enterprise Healthcare Information Systems
6    A The unit is expected to be taken after introductory courses in related units such as COMP5206 Information Technologies and Systems (or COMP5138/COMP9120 Database Management Systems)
Semester 2
HTIN5003
Health Technology Evaluation
6      Semester 2b
COMP9001
Introduction to Programming
6    N INFO1110 OR INFO1910 OR INFO1103 OR INFO1903 OR INFO1105 OR INFO1905 OR ENGG1810
Semester 1
Semester 2
COMP9003
Object-Oriented Programming
6    A COMP9001 OR INFO1110 OR INFO1910
N INFO1113 or INFO1103 or COMP9103
Semester 1
Semester 2
COMP5046
Natural Language Processing
6    A Knowledge of an OO programming language
Semester 1
COMP5048
Visual Analytics
6    A Experience with data structures and algorithms as covered in COMP9103 OR COMP9003 OR COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions)
Semester 1
Semester 2
COMP5318
Machine Learning and Data Mining
6    A INFO2110 OR ISYS2110 OR COMP9120 OR COMP5138
Semester 1
Semester 2
COMP5424
Information Technology in Biomedicine
6    A Experience with software development as covered in SOFT2412 or COMP9103 or COMP9003 (or equivalent UoS from different institutions)
Semester 1
STAT5002
Introduction to Statistics
6    A HSC Mathematics
Semester 1
Semester 2
STAT5003
Computational Statistical Methods
6    A STAT5002 or equivalent introductory statistics course with a statistical computing component

Note: Department permission required for enrolment

Semester 1
Semester 2
BMET9925
AI, Data, and Society in Health
6    A Familiarity with general mathematical and statistical concepts. Online learning modules will be provided to support obtaining this knowledge
N BMET2925
Semester 1
BMET5933
Biomedical Image Analysis
6    A An understanding of biology (1000-level), experience with programming (ENGG1801, ENGG1810, BMET2922 or BMET9922)
Semester 1
Digital Health Electives
BMET5992
Regulatory Affairs in the Medical Industry
6    A MECH3921 OR BMET3921 OR AMME5921 OR BMET5921 and 6cp of 1000-level Chemistry and 6cp of Biology units
N AMME4992 OR AMME5992
Semester 2
IDEA9106
Design Thinking
6      Semester 1
Semester 2
CEPI5100
Introduction to Clinical Epidemiology
6   

Refer to the unit of study outline https://www.sydney.edu.au/units
Intensive February
Intensive July
Semester 1
Semester 2
BETH5204
Clinical Ethics
6   

Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
HPOL5014
Foundations Health Technology Assessment
6   

Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 2
HPOL5012
Leadership in Health
6    A Students are expected to have at least 1 year work experience in a health practice, policy or administrative role


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 2
COMP5427
Usability Engineering
6    A Skills with modelling as covered in ISYS2110 or ISYS2120 or COMP9110 or COMP9201 (or equivalent UoS from different institutions)
Semester 1

Capstone Project units of study

BIDH5001
Digital Health and Data Science Project A
6    A Assumed library information systems research skills and basic knowledge of health, health care and associated ethics and governance systems are required. Students must complete a pre-capstone knowledge screening quiz or interview which will identify recommended modules for their capstone. Please check the Canvas site for this unit for any information on further recommended resources, mandatory sessions and modules
P 24 credit points of (HTIN5006 or HTIN5005 or HSBH5003 or BIDH5000 or INFO5306 or HTIN5003 or COMP9103 or COMP5046 or COMP5048 or COMP5318 or COMP5424 or STAT5002 or STAT5003 or BMET9925 or BMET5933 or BMET5992 or IDEA9106 or CEPI5100 or BETH5204 or HPOL5014 or HPOL5012 or COMP5427)

Note: Department permission required for enrolment
Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2
BIDH5002
Digital Health and Data Science Project B
6    A Assumed library information systems research skills and basic knowledge of health, health care and associated ethics and governance systems are required. Students must complete a pre-capstone knowledge screening quiz or interview which will identify recommended modules for their capstone. Please check the Canvas site for this unit for any information on further recommended resources, mandatory sessions and modules
P 24 credit points of (HTIN5006 or HTIN5005 or HSBH5003 or BIDH5000 or INFO5306 or HTIN5003 or COMP9103 or COMP5046 or COMP5048 or COMP5318 or COMP5424 or STAT5002 or STAT5003 or BMET9925 or BMET5933 or BMET5992 or IDEA9106 or CEPI5100 or BETH5204 or HPOL5014 or HPOL5012 or COMP5427)


Refer to the unit of study outline https://www.sydney.edu.au/units
Semester 1
Semester 2