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This micro-credential includes one full-day session on campus at ANU.


Producing attractive, informative data visualisations is critical to the effective communication of quantitative data. This micro-credential introduces students to modern data exploration tools and strategies using the R language. Enrollees will learn how to quickly, efficiently and reproducibly extract insights from data and produce high-quality data visualisations. These skills will be developed and demonstrated using a range of complex datasets, across a range of applications including public health and the environmental sciences. The skills acquired in this unit are transferable to data from any domain.

Learning outcomes 

Upon successful completion, enrollees will have the knowledge and skills to:

  1. Work confidently within the R environment
  2. Import and manipulate datasets
  3. Create complex, customised visualisations
  4. Write R scripts that allow this work to be reproduced

Indicative assessment 

Enrollees will be provided with an example dataset, and will be tasked with exploring these data, producing a number of informative visualisations, and compiling these into a report alongside code and a brief discussion of each figure (approximately 1000 words total).

Assumed knowledge 

This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.

Micro-credential stack information 

This micro-credential may be undertaken as a stand-alone course.


Course Code: DATA09

Workload: 21 hours 

  • Contact hours: 7 hours
  • Individual study and assessment: 14 hours

ANU unit value: 1 unit

AQF Level: 9

Contact: Professor Eric Stone


This Micro-credential is taught at a graduate level.  This is not an AQF qualification.

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