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Master of Digital Health and Data Science

Unit of study table

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.

 

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

Core units

HTIN5006
Foundations of Healthcare Data Science
6    N HTIN4006
HTIN5005
Applied Healthcare Data Science
6    N HTIN4005
BIDH5003
Foundations of Digital Health
6    N HSBH5003 or HSBH3008 or BIDH3008
BIDH5000
Digital Health Innovation and Implementation
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

Selective units of study (Graduate Certificate)

Data science selectives
HTIN5006
Foundations of Healthcare Data Science
6    N HTIN4006
HTIN5005
Applied Healthcare Data Science
6    N HTIN4005
Digital health selectives
BIDH5003
Foundations of Digital Health
6    N HSBH5003 or HSBH3008 or BIDH3008
BIDH5000
Digital Health Innovation and Implementation
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

Elective units of study

Data science electives
INFO5306
Enterprise Healthcare Information Systems
6    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)
N INFO4406
HTIN5003
Health Technology Evaluation
6    N HTIN4003
COMP9001
Introduction to Programming
6    INFO1110 OR INFO1910 OR INFO1103 OR INFO1903 OR INFO1105 OR INFO1905 OR ENGG1810
COMP9003
Object-Oriented Programming
6    COMP9001 OR INFO1110 OR INFO1910
INFO1113 or INFO1103 or COMP9103
COMP5046
Natural Language Processing
6    Knowledge of an OO programming language
N COMP4446
COMP5048
Visual Analytics
6    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)
N COMP4448 or OCMP5048
COMP5318
Machine Learning and Data Mining
6    A Experience with programming and data structures as covered in COMP2123 OR COMP2823 or COMP9123 (or equivalent unit of study from different institutions).
N COMP4318 or OCMP5318
COMP5424
Information Technology in Biomedicine
6    Experience with software development as covered in SOFT2412 or COMP9103 or COMP9003 (or equivalent UoS from different institutions)
N COMP4424
STAT5002
Introduction to Statistics
6    HSC Mathematics
STAT5003
Computational Statistical Methods
6    STAT5002 or equivalent introductory statistics course with a statistical computing component
BMET9925
AI, Data, and Society in Health
6    Familiarity with general mathematical and statistical concepts. Online learning modules will be provided to support obtaining this knowledge
BMET2925
BMET5933
Biomedical Image Analysis
6    An understanding of biology (1000-level), experience with programming (ENGG1801, ENGG1810, BMET2922 or BMET9922)
Digital health electives
BMET5992
Regulatory Affairs in the Medical Industry
6    MECH3921 OR BMET3921 OR AMME5921 OR BMET5921 and 6cp of 1000-level Chemistry and 6cp of Biology units
AMME4992 OR AMME5992
IDEA9106
Design Thinking
6     
CEPI5100
Introduction to Clinical Epidemiology
6     
BETH5204
Clinical Ethics
6     
HPOL5014
Foundations Health Technology Assessment
6     
HPOL5012
Leadership in Health
6    Students are expected to have at least 1 year work experience in a health practice, policy or administrative role
COMP5427
Usability Engineering
6 N COMP4427

Capstone project units of study

BIDH5001
Digital Health and Data Science Project A
6    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)
BIDH5002
Digital Health and Data Science Project B
6    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)