Data Taming, Modelling and Visualisation

Postgraduate | 2026

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Area/Catalogue
INFO 5043
Course ID icon
Course ID
203975
Level of study
Level of study
Postgraduate
Unit value icon
Unit value
6
Course level icon
Course level
5
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Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No
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Note:
Course data is interim and subject to change

Course overview

A practical introduction to finding relationships in data using statistical methods. The course introduces the principles of taming and tidying data, types of data, exploratory data analysis and visualisation, data transformation, as well as model fitting and interpretation. A focus will be to introduce R programming for data science applications, particularly through real-world case studies.

Course learning outcomes

  • Describe the principles of data taming and approaches used to tidy data.
  • Identify the different types of data and data variables.
  • Select from data analysis and visualisation techniques in order to create a linear model.
  • Interpret data within a linear model to make predictions from the model.
  • Execute techniques to transform, reduce and summarise data in order to visualise it.
  • Articulate the ideas that data scientists consider when looking at data.
  • Communicate professionally on the application of linear models through the use of real-world case studies.

Prerequisite(s)

N/A

Corequisite(s)

N/A

Antirequisite(s)

N/A