Instructor
Data Visualization & Communication
Master of Environmental Data Science (MEDS)
Winter 2025
Artwork by Allison Horst
Course Description
Effectively communicating your work in a responsible, 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 with diverse audiences.
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) data so that it’s appropriately formatted for building data visualizations
- Build effective, responsible, accessible, and aesthetically-pleasing visualizations using the R programming language, and specifically
{ggplot2}+ ggplot2 extension packages - Write code from scratch and read and adapt code written by others
- Apply a DEI (Diversity, Equity & Inclusion) lens to the process of designing data visualizations
- Assess, critique, and provide constructive feedback on data visualizations
Teaching Team
Acknowledgements
Building this course meant learning from the many incredible folks who think a lot about producing effective, beautiful, and responsible data visualizations. I relied heavily on the open source R / {ggplot2} / data viz teaching materials and tutorials that this wonderful data science community shares so willingly. Attribution will be included on any slides / materials where content is adapted from other educators.