RStudio training

Join RStudio Chief Data Scientist Hadley Wickham for his popular “Building tidy tools” workshop in Sydney, Australia! If you’d missed the sold out course at rstudio::conf 2019 now is your chance. Register here: https://www.rstudio.com/workshops/building-tidy-tools/ You should take this class if you have some experience programming in R and you want to learn how to tackle larger-scale problems. You’ll get the most if you’re already familiar with the basics of functions (i.e., you’ve written a few) and are comfortable with R’s basic data structures (vectors, matrices, arrays, lists, and data frames). There is approximately a 30% overlap in the material with Hadley’s previous “R Masterclass”. However, the material has been substantially reorganised, so if you’ve taken the R Masterclass in the past, you’ll still learn a lot in this class.

rstudio::conf 2019 featured 15 workshops on tidyverse, Shiny, R Markdown, modeling and machine learning, deep learning, big data, and what they forgot to teach you about working with R. Some of the new workshops for this year touched on topics like putting Shiny applications into production at scale and R & Tensorflow. The conference also featured certification workshops on RStudio Professional Administrator and Train-the-trainer for tidyverse and Shiny. Below is a list of all workshops we hosted, with links to materials. Even though the materials alone cannot replace the actual workshop experience, we hope that you’ll find them useful. RStudio regularly hosts workshops throughout the year so please subscribe to training updates . You can also find out more about each of the workshops at the conference repository .

Join Jenny Bryan and Jim Hester of RStudio for this two-day hands-on workshop designed for experienced R and RStudio users who want to (re)design their R lifestyle! If you’d missed this sold out course at rstudio::conf 2018 now is your chance. Register here: https://www.rstudio.com/workshops/what-they-forgot-to-teach-you-about-r/ In this workshop you’ll learn holistic workflows that address the most common sources of friction in data analysis. We’ll work on project-oriented workflows, version control for data science (Git/GitHub!), and how to plan for collaboration, communication, and iteration (incl. RMarkdown). In terms of your R skills, expect to come away with new knowledge of your R installation, how to maintain it, robust strategies for working with the file system, and ways to use the purrr package for repetitive tasks.