Learn how to

• explore, groom, visualize, and analyze data
• make all of that reproducible, reusable, and shareable
• using R
  

• Introduction to R and the RStudio IDE; scripts, the workspace, RStudio Projects
• Generate reports from R scripts and R Markdown
• Care and feeding of data in R
• Data manipulation and split-apply-combine with dplyr and tidyr
• Data visualization with ggplot2
• Graphs and descriptive stats for quantitative and categorical variables
• Writing R functions
• Coding style and project organization
• Version control with Git; collaboration via GitHub
• Character data; regular expressions
• Interactive pages, apps, and graphics with Shiny
• Get data off the web and expose data, code, results on the web
• Distribute data and code via an R package
• Automate an analytical pipeline, e.g. via Make
  

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The course organization on GitHub: https://github.com/STAT545-UBC

Repo that creates this website: https://github.com/STAT545-UBC/STAT545-UBC.github.io