This article is originally published at https://www.rstudio.com/blog/
We are so excited for rstudio::conf! To start off the conference in July, we have an amazing line-up of workshops. There’s a session for you wherever you are on your data science journey. Get inspired and learn something new.
You can find all workshop information on the rstudio::conf(2022) website. Please note that while there will be virtual options for the conference, the workshops are only offered in person.
Introduction to the tidyverse ????
Presented by the RStudio Academy Team
A unique 6-week data science apprenticeship where you’ll develop the skills necessary to do data science with the R language.
Learn more about Introduction to the tidyverse.
Getting Started with Shiny ✨
Presented by Colin Rundel
Shiny is an R package that makes it easy to build interactive web apps straight from R. This workshop will start at the beginning.
Learn more about Getting Started with Shiny.
Getting Started with Quarto ????
Presented by Tom Mock
This workshop is designed for those who have no or little prior experience with R Markdown and who want to learn Quarto.
Learn more about Getting Started with Quarto.
From R Markdown to Quarto ????
Presented by Andrew Bray
This workshop is designed for those who want to take their R Markdown skills and expertise and apply them in Quarto, the next generation of R Markdown.
Learn more about From R Markdown to Quarto.
Making Art from Code ????
Presented by Danielle Navarro
This workshop provides a hands-on introduction to generative art in R. You’ll learn artistic techniques that generative artists use regularly in their work including flow fields, iterative function systems, tilings, and more.
Learn more about Making Art from Code.
Designing the Data Science Classroom ????????
Presented by Mine Çetinkaya-Rundel and Maria Tackett
The goal of this workshop is to equip educators with concrete information on content, workflows, and infrastructure for painlessly introducing modern computation with R and RStudio within a data science curriculum.
Learn more about Designing the Data Science Classroom.
Building Tidy Tools ????
Presented by Emma Rand and Ian Lyttle
This is a two-day, hands-on workshop for those who have embraced the tidyverse and want to build their own packages.
Learn more about Building Tidy Tools.
R for People Analytics ????
Presented by Keith McNulty, Alex LoPilato, and Liz Romero
The course will cover some of the most commonly used methods of analysis and inference when working with data related to people, such as survey data and organizational network data.
Learn more about R for People Analytics.
How Data Science with R Works for Systems Administrators ????
Presented by Alex Gold
In this workshop, you’ll learn to use the capabilities of RStudio Team to enable your organization’s R and Python users, including topics like package and environment management, performance and scaling, external data connections, and integrating RStudio Team with CI/CD pipelines.
Learn more about How Data Science with R Works for Systems Administrators.
Graphic Design with ggplot2: How to Create Engaging and Complex Visualizations in R ????
Presented by Cédric Scherer
The workshop covers the most important steps and helpful tips to create visually appealing, engaging and complex graphics with ggplot2.
Learn more about Graphic Design with ggplot2.
What They Forgot to Teach You About R ????
Presented by Shannon McClintock Pileggi, Jenny Bryan, and David Aja
This is a two-day hands on workshop designed for experienced R and RStudio users who want to (re)design their R lifestyle.
Learn more about What They Forgot to Teach You About R.
Building Production-Quality Shiny Applications (almost full!) ????️
Presented by Eric Nantz
This workshop is for the Shiny developer who has entered this stage of their application development journey.
Learn more about Building Production-Quality Shiny Applications.
Machine Learning with tidymodels (almost full!) ????
Presented by Julia Silge, Max Kuhn, and David Robinson
This workshop provides an introduction to machine learning with R.
Learn more about Machine Learning with tidymodels.
Causal Inference in R (almost full!) ➡️
Presented by Lucy D’Agostino McGowan and Malcolm Barrett
In this workshop, we’ll teach the essential elements of answering causal questions in R through causal diagrams, and causal modeling techniques such as propensity scores and inverse probability weighting.
Learn more about Causal Inference in R.
Are you as excited as we are?
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