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How to get RStudio Conference 2020 workshop materials free online

Even if you attended RStudio’s pre-meeting two-day training very last month, you could only attend a single workshop—and there were being far more than half a dozen. Now, however, a lot of components such as slides and R code are accessible 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 variation regulate set up on your system, you can down load a zipped file of any repository. But git and GitHub do make it simpler and far more classy. Look at out episode 33 of Do Far more with R under if you’d like to learn about git and GitHub in RStudio:

Tidy time series and forecasting in R

Teacher Rob J. Hyndman, professor statistics at Monash University, literally wrote the e-book on time series forecasting in R — not to point out the R forecast package deal. I was torn concerning attending this a single and the equipment-learning workshop I ended up getting. Happily, even however it really is not rather as good as becoming in a classroom in man or woman, the written components and code are on-line.

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

Contemporary geospatial details evaluation in R

“You will learn to read, manipulate, and visualize spatial details and you’ll be introduced to features that will have you indicating, ‘I failed to know you could do that in R!’” touts this workshop’s overview. This is another a single I wish I could have attended.

This class featured the sf, tmap, mapview, raster, and dplyr deals.

Most of the workshop details is not on GitHub directly, but there is a fundamental repo at https://github.com/rstudio-conf-2020/geospatial with instructions on how to down load the relaxation.

Workshop leader Zev Ross claimed he posted equally high-res slides for viewing and a PDF variation for down load.

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

Device learning in R

There were being two workshops on equipment learning this yr: an introduction to the even now-evolving tidymodels equipment learning package deal ecosystem and a far more superior session with Max Kuhn, creator of the effectively-acknowledged caret package deal.

Introduction to equipment learning with the tidyverse

This workshop has its very own web page the place you can down load slides, workouts, and options from Alison Hill’s classes: https://conf20-intro-ml.netlify.com/components/. There is also a GitHub repo.

Used equipment learning in R

Max Kuhn’s session has a web page at https://rstudio-conf-2020.github.io/applied-ml/README.html. Toward the leading there are one-way links to see pieces 1 by six separately. There is also a GitHub repo.

Deep learning with Keras and TensorFlow in R

Look at out the sturdy GitHub repo which incorporates a quantity of R Markdown notebooks with code and explanations as effectively as one-way links to slides and details. This was taught by Brad Boehmke, director of details science at 84.51°.

Textual content mining with tidy details principles

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

Huge details evaluation in R

This workshop, taught by RStudio engineer James Blair, targeted on using dplyr with details.table, databases, and Spark for significant-scale details. It also made use of the vroom, dtplyr, and DBI deals.

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

Shiny from begin to end

If you’ve wanted to learn the Shiny R interactive internet framework — or if you’ve labored with it but wanted to up your game — Macalester College or university professor Danny Kaplan’s Shiny workshop GitHub repository characteristics slides and job code. You can also clone the job with a free of charge RStudio Cloud account at https://rstudio.cloud/job/865256.

JavaScript for Shiny people

Also Shiny-linked, this workshop by Garrick Aden-Buie was developed to support people customize fundamental Shiny applications by using JavaScript, HTML, and CSS to make them glimpse far better and do far more. This is another workshop I wish I could have attended. I just cannot hold out to dig into the code. 

In addition to the workshop GitHub repo, there is a js4shiny.com web page that is undoubtedly worth a visit.

R Markdown and interactive dashboards

This two-day workshop by Yihui Xie (creator of several R deals such as knitr and DT and the co-creator of Shiny, R Markdown, and leaflet) and RStudio education director Carl Howe was aimed at aiding attendees develop highly effective interactive paperwork and dashboards.

The objectives, in accordance to the workshop description, integrated the pursuing:

  • The total abilities of R Markdown
  • How to parameterize and publish studies from R Markdown
  • How to develop interactive dashboards using htmlwidgets and Shiny

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

What they forgot to instruct you about R

It appears like an introductory workshop, but this was actually “designed for skilled R and RStudio people who want to (re)design and style their R life-style,” in accordance to the session overview. “You’ll learn holistic workflows that deal with the most widespread sources of friction in details evaluation. We’ll do the job on job-oriented workflows, variation regulate for details science (Git/GitHub), and how to approach for collaboration, conversation, and iteration (such as R Markdown).” Instructors Kara Woo, Jenny Bryan, and Jim Hester are all effectively-acknowledged in the tidyverse earth. 

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

Developing tidy resources

Taught by Charlotte Wickham and Hadley Wickham, this workshop was aimed at “those who have embraced the tidyverse and now want to increase it to satisfy their very own demands,” in accordance to the workshop overview. It discusses API design and style, useful programming resources, the essentials of item design and style in Amazon S3, and the tidy eval system for non-typical evaluation.

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

A realistic introduction to details visualization with ggplot2

This workshop covered “basic principles driving efficient details visualizations” as effectively as learning how to make good graphics with ggplot2. It was taught by Duke University professor Kieran Healy, creator of Details Visualization: A Realistic Introduction. The workshop repo is at https://github.com/rstudio-conf-2020/dataviz.

My organization’s to start with R package deal

If you are intrigued in producing deals at your workplace for “easier details obtain, shared capabilities for details transformation and evaluation, and a widespread glimpse and really feel for reporting,” you may well want to look at out this workshop components by program engineer Rich Iannone and R developer and Ph.D. college student Malcolm Barrett.

You can obtain the GitHub repo at https://github.com/rstudio-conf-2020/my-org-to start with-pkg. 

Workshops for R rookies

R for Excel Users was, not remarkably, a workshop aimed at power Excel people who want to begin incorporating R into their workflow.

And Introduction to Details Science in the Tidyverse, taught by Hadley Wickham and Amelia McNamara, was a “two-day, fingers-on workshop developed for persons who are model new to R and RStudio.”