EPM5033 Programming principles for health data analytics using Python
Faculty of Medicine, Nursing and Health Sciences
EPM5033 Programming principles for health data analytics using Python is a level 5, 6-credit-point, postgraduate unit from the Faculty of Medicine, Nursing and Health Sciences, offered in 2027 in Semester 1 at Caulfield. It has no prerequisites and unlocks 1 unit, leading on to 17 units in all.
- Credit points
- 6
- Offered in 2027
- Semester 1
- Caulfield
- Assessment
- No exam
- 4 tasks
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Requisites
Before EPM5033
Prohibitions
You can't enrol if you have passed any of these.
After EPM5033
1 unit list EPM5033 as a prerequisite or corequisite.
Enrolment rules
Must be enrolled in course M6036 or M6049 or M6030 or M0014 or M6024 or M6028 or M6008 or M6026 or M6009
Overview
You will gain the skills in the Python programming language regularly used in health data analytics. You will be equipped to implement several commonly used Python libraries specifically designed for data manipulation, exploration, visualisation, and machine learning.
You will develop the knowledge and skills of programming in Python, including foundational skills such as programming syntax, functions, data and file management and an introduction to linear and binary regression.
The common Python library packages such as Numpy, Matplotlib and Pandas will be introduced to enable you to describe, visualise, analyse and interpret health data.
Using these industry standard packages, you will investigate contemporary case studies and engage in weekly programming exercises to build your applied skills throughout the unit.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Caulfield | On campus |
Assessment
- 4 x quizzesQuiz / Test20%
- Report: Data frames and visualisationsProject35%
- Report: Regression and classification (2,100 words)Project35%
- Reflection (600 words)Written10%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Apply foundational programming principles using the Python language
- 2
Describe and implement basic elements and various data types in Python
- 3
Investigate and apply relevant Python packages for health data analytics
- 4
Illustrate appropriate data wrangling, visualisation and basic regression techniques in Python for health data analytics
- 5
Solve problems in a variety of health-related contexts using the Python programming language
- 6
Reflect on your learning, and how it might relate to future learning experiences.
- 7
Critically assess and effectively use artificial intelligence (AI) tools responsibly, with transparency and specific to health data analytics
Workload and teaching
- Tutorials-
Twelve hours per week, consisting of (on average):
- 4 hours per week for reading and working through core learning 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 self-directed study (assignment and quiz preparation)
No residential component is required.
Contacts
- Unit Coordinators
- Dr Joanna Dipnall
- Chief Examiners
- Dr Joanna Dipnall
Common questions
What are the prerequisites for EPM5033?
EPM5033 has no prerequisites, but enrolment rules apply.
What can I take after EPM5033?
EPM5033 is a prerequisite or corequisite for 1 unit, including FIT5197. Those lead on to 17 units in all.
When is EPM5033 offered?
In 2027, EPM5033 runs in Semester 1 at Caulfield.
Does EPM5033 have an exam?
No. EPM5033 has 4 assessment tasks and no exam.