ITO5147 Data exploration and visualisation
Faculty of Information Technology
ITO5147 Data exploration and visualisation is a level 5, 6-credit-point, postgraduate unit from the Faculty of Information Technology. It isn't offered in 2026. It has no prerequisites.
- Credit points
- 6
- Offered in 2026
- Other periods
- Monash Online
- Assessment
- No exam
- 4 tasks
This is the 2026 handbook entry. See the 2027 entry.
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Requisites
Before ITO5147
Prohibitions
You can't enrol if you have passed any of these.
After ITO5147
No unit lists ITO5147 as a prerequisite in the 2026 handbook.
Enrolment rules
Prerequisite: Some of the material relies on a basic knowledge of statistics (mean, standard deviation, median) and a basic knowledge of geometry. A secondary/high-school level understanding of these concepts is sufficient. Some knowledge of programming with R is recommended.
Equivalent units
The same content under another code. Only one of them counts.
Overview
This unit introduces statistical and visualisation techniques for the exploratory analysis of data. It will cover the role of data visualisation in data science and its limitations. Visualisation of qualitative, quantitative, temporal and spatial data will be presented. What makes an effective data visualisation, interactive data visualisation, and creating data visualisations with R and other tools will also be presented.
Offerings in 2026
| Teaching period | Campus | Mode |
|---|---|---|
| Teaching period 2 | Monash Online | Mo |
Assessment
- Data Exploration and Visualisation ProposalWritten5%
- DataVis Design and ReflectionArtefact15%
- Data Exploration and Visualisation ProjectProject60%
- QuizQuiz / Test20%
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
Perform exploratory data analysis using a range of visualisation tools;
- 2
Describe the role of data visualisation in data science and its limitations;
- 3
Critically evaluate and interpret a data visualisation;
- 4
Distinguish standard visualisations for qualitative, quantitative, temporal and spatial data;
- 5
Choose an appropriate and effective data visualisation;
- 6
Implement static and interactive data visualisations using R and other tools.
Workload and teaching
- Workshops24 hours
- Teaching approachOnline learning
A minimum of 144 hours over the 6 week teaching period should be used to complete assignments, participating in discussions, private study and revision.
Learning resources
Technology resources
Access to computer facilities allowing programming in R, Python and D3.
Also must be able to run the Respondus lockdown browser.
Contacts
- Chief Examiners
- Dr Sarah Goodwin
Common questions
What are the prerequisites for ITO5147?
ITO5147 has no prerequisites, but enrolment rules apply.
When is ITO5147 offered?
ITO5147 has no offerings listed in the 2026 handbook.
Does ITO5147 have an exam?
No. ITO5147 has 4 assessment tasks and no exam.