Faculty of Engineering

School of Computer Science

Graduate Certificate in Digital Health and Data Science (2022)


Note: This course version applies only to students first enrolling in 2022.
WARNING: This course version is currently under review and is subject to change.


1. Overview

Course: Graduate Certificate in Digital Health and Data Science (2022)
CP Required: 24
Min FT Duration: N/A
Min PT Duration: 1.00 Years
Faculty/School: School of Computer Science
Years Offered: 2025, 2024, 2023, 2022

2. Requirements

The GCDHDS exists primarily as an entry pathway into the Masters program and students complete a subset of the MDHDS units with an expectation that they complete the rest if they progress onto the Masters course.

The GCDHDS comprises 24 credit points of study. These are split equally between data science and digital health topics. They must constitute:

(a) 6 credit points of Data Science Selective units of study

(b) A further 6 credit points of either Data Science Selective or Data Science Elective units of study

(c) 6 credit points of Digital Health Selective units of study

(d) A further 6 credit points of either Digital Health Selective or Digital Health Elective units of study

Completion time

Enrolment in the Graduate Certificate in Digital Health and Data Science may be either part-time or full-time with a maximum completion time of two years.

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
6 Select from Unit Block:
Data Science Selectives
6 Select from Unit Block:
Digital Health Selectives
List
6 Select from Unit Blocks:
Data Science Selectives
Data Science Electives
List
6 Select from Unit Blocks:
Digital Health Selectives
Digital Health Electives

4. Pathways

No streams/majors defined for this course version.

5. Unit Blocks

Block 1 - Data Science Selectives (Min CP: 6,Max CP: 12)

Unit Code Unit Name CP Sessions Offered
HTIN5005 Applied Healthcare Data Science 6 Semester 2
HTIN5006 Foundations of Healthcare Data Science 6 Semester 1

Block 2 - Digital Health Selectives (Min CP: 6,Max CP: 12)

Unit Code Unit Name CP Sessions Offered
BIDH5000 Digital Health Innovation and Implementation 6 Semester 2
HSBH5003 eHealth for Health Professional 6 Semester 1

Block 3 - Data Science Electives (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
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 4 - Digital Health Electives (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.