by the RStudio Academy team of data science educators, including Garrett Grolemund, Desirée De Leon, and others
🗓️ In-person workshop: July 25 and 26, 2022
⏰ 09:00 - 17:00
🏨 [ADD ROOM]
✍️ rstd.io/conf
Important: This event is a 6 week experience that requires weekly virtual meetings from the weeks of July 5 to August 16.
Join RStudio Academy for a unique 6-week data science apprenticeship where you’ll develop the skills necessary to do data science with the R language. This program focuses on completing a hands-on project that you tackle one week at a time under the close guidance of a mentor.
Academy is designed to build skills that you retain long-term: through a combination of interactive lessons, applied project work, group sessions, and check-ins with a mentor – each of which occurs on a weekly basis – you will gain comfort with R and its fundamental Tidyverse packages. This learning experience is primarily virtual, with two in-person days during rstudio::conf2022. It will be taught by the RStudio Academy team of data science educators, including Garrett Grolemund, Desirée De Leon, and others. Subjects will include importing, tidying, and transforming data with the Tidyverse, visualizing data with ggplot2, modeling data with base R, and reporting findings reproducibly with R Markdown. Begins last week of June 2022. No knowledge of R required.
Each week of this course will give you practice with a new set of tools from R and the tidyverse:
- R Basics - Explore the basic components of R, including objects, functions, and packages.
- Read and visualize - Import and visualize data with readr and ggplot2.
- Transform tables - Transform data with dplyr.
- Conf in-person practice - Perform exploratory data analysis with the tools of the tidyverse.
- Joins and tidying - Join datasets and tidy data with dplyr and tidyr.
- Model and publish - Fit a basic model and build polished reports with R Markdown.
Time commitment:
This is a 6 week course that runs from July 5 through the week of August 16, and includes two in-person days. This course requires:
- A virtual kickoff event on July 5, 2022 at 12p EDT
- 3 - 5 hours of asynchronous learning per week
- Group sessions that meet each week for 1 hour over Zoom
- After registration, you will be able to sign up for a recurring Group Session time on our workshop website as they become available. Enrolling in a Group Session is required to complete your registration for this workshop.
Consider these questions:
- You have a dataset of prices of diamonds, as well as their size. Could you make a scatterplot of the two variables using ggplot2?
- You have two datasets, one with information on music genres and age ranges, the other with genres and radio station call names. Can you imagine how you would join them together with a dplyr verb?
- We want to model the wages of people in the United States, using their height and education as predictors. Then, we would like to plot model predictions for each level of educational attainment. Can you imagine how to do this in R?
If you answered "no" to any/all of those questions... great! This Academy experience is for you. By the end of the 6 weeks, you should be able to accomplish all those tasks. If you answered "yes" to all three questions, you may want to consider taking a different workshop.
Please refer to the course website for pre-work to be completed before rstudio::conf(2022).
| Time | Activity |
|---|---|
| 09:00 - 10:30 | Session 1 |
| 10:30 - 11:00 | Coffee break |
| 11:00 - 12:30 | Session 2 |
| 12:30 - 13:30 | Lunch break |
| 13:30 - 15:00 | Session 3 |
| 15:00 - 15:30 | Coffee break |
| 15:30 - 17:00 | Session 4 |
| Time | Activity |
|---|---|
| 09:00 - 10:30 | Session 1 |
| 10:30 - 11:00 | Coffee break |
| 11:00 - 12:30 | Session 2 |
| 12:30 - 13:30 | Lunch break |
| 13:30 - 15:00 | Session 3 |
| 15:00 - 15:30 | Coffee break |
| 15:30 - 17:00 | Session 4 |
The RStudio Academy team of data science educators, including Garrett Grolemund, Desirée De Leon, and others.
To preview the course website locally, you will first need to install Quarto. Then run the following in your RStudio Console:
quarto::quarto_preview(file = "site")
