UnitLevel 5Postgraduate

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 2025 in Semester 1 at Caulfield. It has no prerequisites and unlocks 1 unit, leading on to 16 units in all.

Credit points
6
Offered in 2025
Semester 1
Caulfield
Assessment
No exam
4 tasks

This is the 2025 handbook entry. See the 2027 entry.

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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 (Master of Health Data Analytics)

Overview

The Python programming language is an important programming language in health data analytics. 
Python is a widely-used open-source data science software which can handle large datasets.
There are several Python libraries specifically designed for data manipulation, exploration, visualization, 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 2025

Teaching periodCampusMode
First semesterCaulfieldOn campus

Assessment

  • Report: Data frames and visualisationsWritten
    35%
  • Report: Regression and classificationWritten
    35%
  • 4 x QuizzesQuiz / Test
    20%
  • Reflection (600 words)Written
    10%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    Apply foundational programming principles using the Python language

  2. 2

    Describe and implement basic elements and various data types in Python

  3. 3

    Investigate and apply relevant Python packages for health data analytics

  4. 4

    Apply appropriate data wrangling, visualisation and basic regression techniques in Python for health data analytics

  5. 5

    Solve problems in a variety of health-related contexts using the Python programming language

  6. 6

    Reflect on your work to describe your learning, and how it might relate to future learning experiences

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 16 units in all.

When is EPM5033 offered?

In 2025, EPM5033 runs in Semester 1 at Caulfield.

Does EPM5033 have an exam?

No. EPM5033 has 4 assessment tasks and no exam.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Medicine, Nursing and Health Sciences
Organisational unit
Department of Epidemiology and Preventive Medicine
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 2
Study abroad
Not available
Handbook years
202520262027