D-Lab's Fast-R Workshop

https://dlab.berkeley.edu

Need to get up to speed with R in a hurry? This is D-Lab's two-hour introduction to R basics for basic research workflows!

Setup

1. Install R: https://cloud.r-project.org/

2. Install RStudio Desktop Open Source License Free: https://rstudio.com/products/rstudio/download/

3. Download the Fast-R materials. Visit https://github.com/dlab-berkeley/Fast-R

• Click the green "Code" button
• Click "Download ZIP"
• Extract this file someplace familiar (e.g., Desktop)

If you are a Git user, you can clone this repository by opening a terminal, cd into the correct location, and type: git clone git@github.com:dlab-berkeley/Fast-R.git

Start running the code

Open the file "Fast-script.R" to begin. Place your cursor on a line of runnable code (lines without hashtags preceding them) and click the "Run" button or press Ctrl + Enter (PC) or command + Enter (Mac) to run a line of code. The output will appear in the "Console" section of RStudio.

Be sure to also utilize free services for UC Berkeley students, faculty, and staff:

• The D-Lab workshop calendar: https://dlab.berkeley.edu/calendar-node-field-date

• D-Lab consulting services: https://dlab.berkeley.edu/consulting

Other D-Lab R workshops

Beginner

• R Fundamentals

Basic Competency

• R Data Wrangling
• R Graphics with ggplot2
• R Functional Programming
• Project Management in R
• Geospatial Fundamentals in R with sf
• Census Data in R

Intermediate/Advanced Competency

• Advanced Data Wrangling in R
• Introduction to Machine Learning in R
• Unsupervised Learning in R
• R Machine Learning with tidymodels
• Introduction to Deep Learning in R
• R Package Development

Resources

• Kearns GJ. 2010. Introduction to Probability and Statistics in R

• James G, Witten D, Hastie T, Tibshirani R. 2013. An Introduction to Statistical Learning: With Applications in R, 7th edition