Effectively communicating your work in an accessible and visually pleasing way is often (if not, always) a central part of data science. This course will focus on the basic principles for effective communication through data visualization and using technical tools and workflows for creating and sharing data visualizations. ……..
Learning Outcomes:
By the end of this course, learners should be able to:
Identify which types of visualizations are most appropriate for your data and your audience
Prepare (e.g. clean, explore, wrangle, model) data so that it’s appropriately formatted for building data visualizations
Build effective, aesthetically-pleasing, and accessible visualizations using the R programming language, and specifically {ggplot2} + ggplot2 extension packages
Apply a DEI (Diversity, Equity & Inclusion) lens to the process of designing data visualizations
Write code from scratch and read and adapt code written by others
Assess, critique, and provide constructive feedback on data visualizations
Description:
Effectively communicating your work in an accessible and visually pleasing way is often (if not, always) a central part of data science. This course will focus on the basic principles for effective communication through data visualization and using technical tools and workflows for creating and sharing data visualizations. ……..
Learning Outcomes:
By the end of this course, learners should be able to:
{ggplot2}
+ggplot2
extension packages