The bootcamp gives a gentle introduction to R and RStudio, transforming and visualizing data with the tidyverse, and the basics of R Markdown. It assumes no prior experience with R or any other programming language and is designed to get learners up and running with the most widely useful tools for reproducible data analysis in R while emphasizing best practices for writing code and organizing project-oriented workflows.
It also contains a curated list of resources for each topic for those who want more opportunities for further learning and practice. The materials have been designed such that you should be able to work through the slides and exercises at your own pace if you were not able to attend the bootcamp sessions.
Much of the content was adapted from Brendan Cullens Intro to R Boot Camp. I also adapted content from a variety of other sources, including R for Data Science, Modern Dive, Alison Hill's R Markdown for Medicine workshop, Michael Frank's R Markdown workshop, and Sylvia Canelón's Intro to the Tidyverse presentation for R-Ladies Chicago.
This website was based on a template demo course website created by Alison Hill as part of an RStudio Webinar along with Desirée De Leon. All artwork, unless otherwise noted, is by Allison Horst. Note boxes were created following a tutorial by Desirée De Leon. I also borrowed some custom CSS from Emi Tanaka.
Slides were created using {xaringan} by Yihui Xie and {xaringanExtra} by Garrick Aden-Buie. I also used {flipbookr} by Gina Reynolds for making ggplot flipbooks and {flair} by Kelly Bodwin for color-coding.
The code of conduct for this bootcamp was adapted from Cascadia R Conf.
Thanks also to Mine Çetinkaya-Rundel for her resources on using RStudio Cloud and Greg Wilson for organizing the collection of data science concept maps.
The materials shared here are free and open source and may be shared and adpated under the Creative Commons License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
