Course Details

  • Date: November 10th, 2020 - November 10th, 2020
  • Time: 11:00 am - 1:00 pm
  • Location: Online Webinar
  • Presenter(s): Amy Stonelake (BTEP), George Zaki (FNLCR)

Link for ALL class sessions including help sessions.

Meeting number: 172 866 2623
Password: NYy4m3V3i3*
Dial in: 650-479-3207

The goal of this workshop is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.

This is very important! Please follow this link and install R and Rstudio onto your computer before class. If you have trouble doing this please send email to and we will help you.

This class is held weekly for 6 weeks. When you register, you are registering for all 6 weeks. Please make sure you have time in your schedule to commit to this training.

Nov 3, 11 AM – 1 PM, Week 1, Introduction to R and RStudio, Project Management with RStudio and Seeking Help (link to recording)
Nov 10, 11 AM – 1 PM, Week 2, Data Structures, Exploring Data Frames and Subsetting Data
Nov 17, 11 AM – 1 PM, Week 3, Creating Publication-Quality Graphics with ggplot2
Nov 24 NO CLASS Thanksgiving Holiday

Dec 1, 11 AM – 1 PM, Week 4, Control Flow, Vectorization and Functions Explained
Dec 8, 11 AM – 1 PM, Week 5, Writing Data, Dataframe Manipulation with dplyr and Dataframe Manipulation with tidyr
Dec 15,11 AM – 1 PM, Week 6, Producing Reports with knitr and Writing Good Software

For more information and class updates, please see the GitHub page for the class at

Help Sessions
Nov 5, 12 – 1 PM, Week 1, Setting up access to the Course Materials with Git, Questions from Week 1
Nov 12, 12 – 1 PM, Week 2
Nov 19, 12 – 1 PM, Week 3
Dec 3, 12 – 1 PM, Week 4
Dec 10, 12 – 1 PM, Week 5
Dec 17, 12 – 1 PM, Week 6