Tidy Data Science with the tidyverse and tidymodels

Summer Stats Camp

by Jake Thompson

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🗓️ June 14-18, 2021
⏰ 09:00 - 16:30
✍️ https://tidyds-2021.wjakethompson.com

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Overview

This workshop provides a gentle introduction to data science using the R statistical programming language. In the first part of the workshop, you'll learn how to tidy, transform, and visualize data. We'll focus on best practices and methods that can be applied to wide range of data sets, using a suite of R packages known as the tidyverse. Tidyverse packages, like dplyr, tidyr, and ggplot2 provide a grammar of data manipulation and visualization. In the second half of the workshop, we will focus on using data to make predictions with another suite of packages known as tidymodels. Like the tidyverse, tidymodels packages, such as parsnip, recipes, and rsample provide a grammar for modeling. Further, the tidymodels packages work seamlessly with the tidyverse packages. Throughout the workshop, students will learn how to combine text and R code in reproducible documents with rmarkdown.

Learning objectives

Students will learn to manage and visualize data and use model to make predictions from several common statistical models using the tidyverse and tidymodels suites of packages.

Is this course for me?

This workshop is appropriate for attendees who answer yes to the questions below:

• Are you new and R and want to learn how to explore, visualize, and model data?

• Are you familiar with R, but want to learn how the tidyverse and tidymodels can take you to the next level?

If you answered yes to either question, you are in the right place! If you are already familiar with the tidyverse and/or tidymodels and want more than an introduction, this course might not be for you.

Prework

The course will be taught over Zoom, so make sure you have stable internet connection. Please make sure you have computer or laptop that has the following installed:

• A recent version of R (>=4.0.0), which is available for free at cran.r-project.org

• A recent version of RStudio Desktop (>=1.4), available for free at www.rstudio.com/download (RStudio Desktop Open Source License)

• The R packages we will use, which you can install by connecting to the internet, opening RStudio, and running at the command line:

  install.packages(c("tidyverse", "tidymodels", "fivethirtyeight",
                     "ggthemes", "babynames", "nycflights13", "skimr",
                     "AmesHousing", "rpart", "ranger", "kknn",
                     "palmerpenguins", "vip", "themis", "modeldata",
                     "parallel", "doParallel", "reprex"),
                   dependencies = TRUE)
  

And don’t forget your power cord!

Schedule

Time	Activity
09:00 - 10:00	Session 1
10:00 - 10:15	Coffee break
10:15 - 12:00	Session 2
12:00 - 13:30	Lunch break
13:30 - 14:30	Session 3
14:30 - 14:45	Coffee break
14:45 - 15:30	Session 4

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This work is licensed under a Creative Commons Attribution 4.0 International License.