I spend a lot of time teaching and preparing for teaching. This past year (2020-21), I tried to put a lot of my materials online. I would love to hear if you use my resources and found them helpful. Or, if there’s a mistake you find or a suggestion you have, I’d love to hear about those, too.

Introduction to Data Science

This course focuses on using data to tell a story. Students use R to wrangle and graph data, using packages including {tidyverse}, {ggmap}, {leaflet}, {gganimate}, {shiny}, and more. The website includes “tutorials” for each unit, and each tutorial includes introductory slides or text/code right in the document, screencasts where I walk through examples of the new code, and example problems with solutions.

Advanced Data Science in R

This course requires Introduction to Data Science and Statistical Machine Learning as prerequisites. It builds on BOTH courses. The website mostly contains materials about modeling, since that is the part of the course I prepared. In small groups, students taught the class about topics (involving R) used in data analysis. In spring of 2021, some of the topics included {tmap}, mapping using geom_sf(), regular expressions, and {tidytext}. Students also made websites using R, created shiny apps, and did a culminating project.

Tidy Tuesday in Thirty

Ok, this isn’t really teaching material, but maybe it will help you learn tidyverse coding. For eight weeks in 2020-2021 (and hopefully starting again, soon!), I did screencasts working with the Tidy Tuesday data of the week. I only gave myself 30 minutes … and maybe a little time after for some final touches. Links to the code and videos are on my Github page.