Faculty of Engineering

School of Computer Science

Master of Digital Health and Data Science (2023)


Note: This course version applies only to students first enrolling in 2023.
WARNING: This course version is currently under review and is subject to change.


1. Overview

Course: Master of Digital Health and Data Science (2023)
CP Required: 48
Min FT Duration: N/A
Min PT Duration: 2.00 Years
Faculty/School: School of Computer Science
Years Offered: 2025, 2024, 2023, 2022

2. Requirements

To qualify for the award of the Master of Digital Health and Data Science candidates must complete 48 credit points of units of study including:

(a) 24 credit points of Core units of study;

(b) 12 credit points of Data Science or Digital Health Elective units of study; and

(c) 12 credit points of Capstone Project units.

Capstone Project

The Capstone Project should be completed in the latter stages of the program: at least 24 credit points total and at least 12 credit points of Core units should be completed prior to undertaking the Capstone.

Completion time

Master of Digital Health and Data Science comprises 48 credit points which can be completed within one year of full-time study. Part-time study is permitted. Students can enter the program at either semester.

For further details of course rules, see the Faculty Handbook at http://sydney.edu.au/handbooks

3. Semesters

Year 1 - Semester 1

Type CP CP From
Core
6 BIDH5003: Foundations of Digital Health
Core
6 HTIN5006: Foundations of Healthcare Data Science
6 Select from Unit Block:
Data Science Electives
6 Select from Unit Block:
Digital Health Electives

Year 1 - Semester 2

Type CP CP From
Core
6 BIDH5000: Digital Health Innovation and Implementation
Core
6 HTIN5005: Applied Healthcare Data Science
12 Select from BIDH5001: Digital Health and Data Science Project A
BIDH5002: Digital Health and Data Science Project B

4. Pathways

No streams/majors defined for this course version.

5. Unit Blocks

Block 1 - Core Units (Min CP: 24,Max CP: 24)

Unit Code Unit Name CP Sessions Offered
BIDH5000 Digital Health Innovation and Implementation 6 Semester 2
HSBH5003 eHealth for Health Professional 6 Semester 1
HTIN5005 Applied Healthcare Data Science 6 Semester 2
HTIN5006 Foundations of Healthcare Data Science 6 Semester 1

Block 2 - Data Science Electives (Min CP: 6,Max CP: 6)

Unit Code Unit Name CP Sessions Offered
BMET5933 Biomedical Image Analysis 6 Semester 1
BMET9925 AI, Data, and Society in Health 6 Semester 1
COMP5046 Natural Language Processing 6 Semester 1
COMP5048 Visual Analytics 6 Semester 1
Semester 2
COMP5318 Machine Learning and Data Mining 6 Semester 1
Semester 2
COMP5424 Information Technology in Biomedicine 6 Semester 1
COMP9001 Introduction to Programming 6 Semester 1
Semester 2
COMP9003 Object-Oriented Programming 6 Semester 1
Semester 2
HTIN5003 Health Technology Evaluation 6 Semester 2b
Semester 2 Block Mode
INFO5306 Enterprise Healthcare Information Systems 6 Semester 2
STAT5002 Introduction to Statistics 6 Semester 1
Semester 2
STAT5003 Computational Statistical Methods 6 Semester 1
Semester 2

Block 3 - Digital Health Electives (Min CP: 6,Max CP: 6)

Unit Code Unit Name CP Sessions Offered
BETH5204 Clinical Ethics 6 Semester 1
BMET5992 Regulatory Affairs in the Medical Industry 6 Semester 2
CEPI5100 Introduction to Clinical Epidemiology 6 Semester 1
Semester 2
COMP5427 Usability Engineering 6 Semester 1
HPOL5012 Leadership in Health 6 Semester 2
HPOL5014 Foundations Health Technology Assessment 6 Semester 2
IDEA9106 Design Thinking 6 Semester 1
Semester 2

Note: In exceptional circumstances, departmental permission may be sought and given for enrolment in an alternative relevant elective unit of study.

Block 4 - Capstone Project (Min CP: 12,Max CP: 12)

Unit Code Unit Name CP Sessions Offered
BIDH5001 Digital Health and Data Science Project A 6 Semester 1
Semester 2
BIDH5002 Digital Health and Data Science Project B 6 Semester 1
Semester 2