Learning Outcomes

[samanthacsik]

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:

• 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

[samanthacsik]

closing this because this has been integrated into (and expanded on) in the course syllabus draft