rstudio::conf 2019 Workshop materials now available
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.
| Workshop | Instructor(s) |
|---|---|
| Introduction to Data Science in the Tidyverse | Amelia McNamara, Hadley Wickham |
| Building Tidy Tools | Charlotte Wickham, Hadley Wickham |
| What They Forgot to Teach You About R | Jenny Bryan, Jim Hester |
| Intro to Shiny and RMarkdown | Danny Kaplan |
| Advanced R Markdown | Alison Hill, Yihui Xie |
| Intermediate Shiny | Aimee Gott, Winston Chang |
| Using Shiny in Production | Kelly O’Briant, Sean Lopp |
| Applied Machine Learning | Max Kuhn, Alex Hayes, Davis Vaughan |
| Introduction to Deep Learning + Beyond the Basics | Sigrid Keydana, Kevin Kuo, Rick Scavetta |
| Big Data with R | Edgar Ruiz, James Blair |
| Train-the-Trainer Certification Workshop | Greg Wilson |
| Shiny Train-the-Trainer Certification Workshop | Mine Çetinkaya-Rundel |
| Tidyverse Train-the-Trainer Certification Workshop | Garrett Grolemund |
Mine Çetinkaya-Rundel
Her work has transformed how data science is taught, emphasizing openness, reproducibility, and hands-on learning. She’s a co-author of influential open textbooks like R for Data Science and OpenIntro Statistics, which have guided countless learners on their journey into statistics and data science.
Mine’s contributions to education and open science have earned her several accolades, including the Waller Education Award by the American Statistical Association, the Robert V. Hogg Award by the Mathematical Association of America, and the Pickard Award by Harvard University's Department of Statistics, honoring her innovative teaching and dedication to expanding access to statistics and data science education.
Through her teaching, open-source work, and advocacy, Mine continues to inspire new generations of data scientists to not only analyze data—but to do so with curiosity, creativity, and purpose.
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