EPM5029 introduction to health data analytics
Faculty of Medicine, Nursing and Health Sciences
EPM5029 introduction to health data analytics is a level 5, 6-credit-point, postgraduate unit from the Faculty of Medicine, Nursing and Health Sciences, offered in 2022 in Semester 1 and Semester 2 at Alfred Hospital. It has no prerequisites.
- Credit points
- 6
- Offered in 2022
- Semester 1, Semester 2
- Alfred Hospital
- Assessment
- No exam
- 4 tasks
This is the 2022 handbook entry. See the 2027 entry.
Reviews
No reviews yetNo reviews yet. Be the first to review EPM5029.
Requisites
Before EPM5029
No prerequisites or corequisites besides the enrolment rules below.
After EPM5029
No unit lists EPM5029 as a prerequisite in the 2022 handbook.
Enrolment rules
Must be enrolled in M6036 Master of Health Data Analytics
Overview
This unit provides you with a foundation for the study of Health Data Analytics by introducing key health, statistical and machine learning concepts. The unit commences with a discussion of the scope of health data analytics, to introduce you to the key ethical and privacy issues, provide you with a review of basic statistics and give you an overview of machine learning techniques and their applications. You will be presented with the classification of health data analytics tasks into description, prediction and explanation.
You will be introduced to the different sources of health data, including linked data, together with the appropriate methods for analysis and strengths and weaknesses surrounding their use. You will be involved in a discussion about the fast-changing nature of data analytics and current topics of major interest including precision and evidence-based medicine and the surge in data-driven evaluation and policy.
Offerings in 2022
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Alfred Hospital | On campus |
| Second semester | Alfred Hospital | On campus |
Assessment
- Written assessment: Health data sources (Equivalent 2,100 words)35%
- Written assessment: Literature review (Equivalent 2,100 words)35%
- Written assessment: Ethics and Privacy (Equivalent 900 words)15%
- Quizzes x 3 (10 questions per quiz each worth 5%)15%
Learning outcomes
When you finish this unit, you should be able to:
- 1
Explain the appropriate use of health data analytics in health research.
- 2
Describe the importance of ethics and privacy with health data analytics.
- 3
Evaluate different health data sources for health data analytics.
- 4
Differentiate between descriptive, predictive and explanatory research problems, and statistical compared with machine learning models.
- 5
Differentiate between descriptive, predictive and explanatory research problems, and statistical compared with machine learning models.
- 6
Describe the steps in data analytics.
Workload and teaching
Twelve hours per week, consisting of (on average)
- 4 hours per week for reading core material
- 1-hour online lecture materials (multiple videos)
- 2-hour face-to-face tutorial
- 2 hours per week for online communication via online moderated discussions, and
- 3 hours per week for assignment and quiz preparation
No residential component is required.
Contacts
- Unit Coordinators
- Dr Jo Dipnall
- Chief Examiners
- Dr Jo Dipnall
Common questions
What are the prerequisites for EPM5029?
EPM5029 has no prerequisites, but enrolment rules apply.
When is EPM5029 offered?
In 2022, EPM5029 runs in Semester 1 and Semester 2 at Alfred Hospital.
Does EPM5029 have an exam?
No. EPM5029 has 4 assessment tasks and no exam.