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. Enrollee's 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 transferrable to data from any domain.
Upon successful completion, enrollee's will have the knowledge and skills to:
- Work confidently within the R environment
- Import and manipulate datasets
- Create complex, customised visualisations
- Write R scripts that allow this work to be reproduced
Enrollee's 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).
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.