How to get RStudio Conference 2020 workshop materials free online

Even if you attended RStudio’s pre-conference two-working day coaching very last thirty day period, you could only go to a person workshop—and there were extra than fifty percent a dozen. Now, however, many components which includes slides and R code are available free of charge on line. Here’s how to get them.

Most of the code and slides have been posted on GitHub. If you really don’t have git model manage established up on your process, you can obtain a zipped file of any repository. But git and GitHub do make it simpler and extra exquisite. Examine out episode 33 of Do Much more with R beneath if you’d like to study about git and GitHub in RStudio:

Tidy time series and forecasting in R

Instructor Rob J. Hyndman, professor stats at Monash University, basically wrote the book on time series forecasting in R — not to point out the R forecast offer. I was torn in between attending this a person and the machine-finding out workshop I ended up taking. Happily, even however it can be not quite as excellent as remaining in a classroom in individual, the prepared components and code are on line.

The GitHub repository is at https://github.com/rstudio-conf-2020/time-series-forecasting and his Forecasting Ideas and Follow textbook is free of charge on line at  https://otexts.com/fpp3/.

Modern-day geospatial info analysis in R

“You will study to read through, manipulate, and visualize spatial info and you’ll be introduced to features that will have you declaring, ‘I failed to know you could do that in R!’” touts this workshop’s overview. This is a different a person I would like I could have attended.

This class highlighted the sf, tmap, mapview, raster, and dplyr packages.

Most of the workshop facts is not on GitHub right, but there is a basic repo at https://github.com/rstudio-conf-2020/geospatial with instructions on how to obtain the relaxation.

Workshop leader Zev Ross claimed he posted each substantial-res slides for viewing and a PDF model for obtain.

See facts at the base of this page on how to obtain and put in the workshop R package with workouts and options.

Equipment finding out in R

There were two workshops on machine finding out this calendar year: an introduction to the nevertheless-evolving tidymodels machine finding out offer ecosystem and a extra state-of-the-art session with Max Kuhn, creator of the perfectly-regarded caret offer.

Introduction to machine finding out with the tidyverse

This workshop has its personal web-site wherever you can obtain slides, workouts, and options from Alison Hill’s sessions: https://conf20-intro-ml.netlify.com/components/. There is also a GitHub repo.

Used machine finding out in R

Max Kuhn’s session has a web-site at https://rstudio-conf-2020.github.io/applied-ml/README.html. Towards the prime there are one-way links to see sections 1 via six independently. There is also a GitHub repo.

Deep finding out with Keras and TensorFlow in R

Examine out the strong GitHub repo which consists of a number of R Markdown notebooks with code and explanations as perfectly as one-way links to slides and info. This was taught by Brad Boehmke, director of info science at 84.51°.

Text mining with tidy info rules

Julia Silge, co-author of Text Mining with R, led this workshop. Her slides are at http://little bit.ly/silge-rstudioconf-1 (Working day 1) and bit.ly/silge-rstudioconf-2 (Working day two). The GitHub repo at https://github.com/rstudio-conf-2020/textual content-mining includes slides and R Markdown paperwork with code.

Major info analysis in R

This workshop, taught by RStudio engineer James Blair, targeted on working with dplyr with info.desk, databases, and Spark for substantial-scale info. It also employed the vroom, dtplyr, and DBI packages.

The GitHub repo at https://github.com/rstudio-conf-2020/significant-data includes an intro, slides, and workbook directory with R Markdown paperwork. The workshop workouts and code are also available as on on line book at https://rstudio-conf-2020.github.io/significant-info/introduction-to-vroom.html.

Shiny from start to end

If you have required to study the Shiny R interactive world wide web framework — or if you have labored with it but required to up your activity — Macalester College or university professor Danny Kaplan’s Shiny workshop GitHub repository attributes slides and undertaking code. You can also clone the undertaking with a free of charge RStudio Cloud account at https://rstudio.cloud/undertaking/865256.

JavaScript for Shiny customers

Also Shiny-relevant, this workshop by Garrick Aden-Buie was intended to assistance customers personalize basic Shiny apps by working with JavaScript, HTML, and CSS to make them seem greater and do extra. This is a different workshop I would like I could have attended. I cannot wait around to dig into the code. 

In addition to the workshop GitHub repo, there is a js4shiny.com web-site that is certainly truly worth a go to.

R Markdown and interactive dashboards

This two-working day workshop by Yihui Xie (creator of several R packages which includes knitr and DT and the co-author of Shiny, R Markdown, and leaflet) and RStudio training director Carl Howe was aimed at aiding attendees produce powerful interactive paperwork and dashboards.

The objectives, according to the workshop description, integrated the following:

  • The complete capabilities of R Markdown
  • How to parameterize and publish experiences from R Markdown
  • How to produce interactive dashboards working with htmlwidgets and Shiny

The workshop GitHub repo at https://github.com/rstudio-conf-2020/rmarkdown-dashboard includes a components directory with slides, workouts, cheat sheets, and extra.

What they forgot to train you about R

It appears like an introductory workshop, but this was truly “designed for experienced R and RStudio customers who want to (re)design and style their R life-style,” according to the session overview. “You’ll study holistic workflows that handle the most typical resources of friction in info analysis. We’ll perform on undertaking-oriented workflows, model manage for info science (Git/GitHub), and how to plan for collaboration, communication, and iteration (which includes R Markdown).” Instructors Kara Woo, Jenny Bryan, and Jim Hester are all perfectly-regarded in the tidyverse planet. 

Find the GitHub repository at https://github.com/rstudio-conf-2020/what-they-forgot and “the a person real URL that one-way links to every little thing!” at https://rstd.io/wtf-2020-rsc.

Constructing tidy equipment

Taught by Charlotte Wickham and Hadley Wickham, this workshop was aimed at “those who have embraced the tidyverse and now want to grow it to meet up with their personal requires,” according to the workshop overview. It discusses API design and style, functional programming equipment, the principles of item design and style in Amazon S3, and the tidy eval process for non-common analysis.

There is a GitHub repo with slides, R Markdown paperwork, and extra.

A realistic introduction to info visualization with ggplot2

This workshop protected “basic rules at the rear of productive info visualizations” as perfectly as finding out how to make excellent graphics with ggplot2. It was taught by Duke University professor Kieran Healy, author of Details Visualization: A Functional Introduction. The workshop repo is at https://github.com/rstudio-conf-2020/dataviz.

My organization’s initial R offer

If you are interested in generating packages at your office for “easier info accessibility, shared features for info transformation and analysis, and a typical seem and truly feel for reporting,” you could want to test out this workshop components by computer software engineer Loaded Iannone and R developer and Ph.D. scholar Malcolm Barrett.

You can find the GitHub repo at https://github.com/rstudio-conf-2020/my-org-initial-pkg. 

Workshops for R rookies

R for Excel Users was, not astonishingly, a workshop aimed at electrical power Excel customers who want to start incorporating R into their workflow.

And Introduction to Details Science in the Tidyverse, taught by Hadley Wickham and Amelia McNamara, was a “two-working day, palms-on workshop intended for folks who are brand new to R and RStudio.”