Help Your Analysts Learn R

My on-site training can help your team become proficient R programmers.

Training engagements start with a discussion about why you want your team to learn R, your team's current capabilities and the type of analyses that they normally do. We then work together to create a curriculum that will meet your team where it is now, and take them to where they need to be. Additionally, my trainings normally incorporate data that staff are likely to encounter in their day-to-day work.

You can learn more about my training philosophy by taking my free course Help Your Team Learn R


Courses

Here is a list of topics I can teach your team:

Tidyverse

Introduction to RStudio and the Tidyverse (1 day)

This courses teaches people the basics programming in R as well as data visualization with ggplot2, data manipulation with dplyr and how to import data from Excel and CSV files into R. Students also leave with a strong understanding of the RStudio IDE, R packages and the Tidyverse. Base R is covered only to the extent necessary to work with the Tidyverse. 

Intermediate R

Intermediate R (1 day)

Students gain a deeper understanding of the R programming language. We cover basic types (numeric, character, logical, factor) as well as data structures (vector, data frame, list).  Vectorization and working with dataframes in base R (e.g. [[ and $). Conditional logic, writing functions, variable scoping and environments. String manipulation with stringr. Working with dates and times with lubridate.

RMarkdown &
Shiny

Sharing Analyses with RMarkdown and Shiny (1 day)

Many analysts generate graphics in Excel and then cut and paste them into Word for presentation. This courses teaches two powerful alternatives that R offers for the same task: RMarkdown (for static documents) and Shiny (for interactive web apps). The Markdown language. Embedding R code in Markdown. Knitting files with knitr. YAML, Chunks and Chunk Options. Creating web applications with Shiny. Client vs. Server programming. Adding UI elements and connecting them to the server.

Census Data

Working with Census Data in R (1 day)

Introduction to the three most popular Census datasets (Decennial Census, American Community Survey and Population Estimates Program). Accessing the data via American Fact Finder. Census geography. Accessing and visualizing the data in R via choroplethr, tidycensus and tigris.

Package Development

Package Development (1 day)

Creating your own R package using devtools and roxygen2. Build and Check. Required files (e.g. Description), exporting functions and creating documentation. 

SQL

SQL (1 day)

(Course is currently being developed).