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Data Matters Courses

I’ve taught the following three courses for Data Matters a week-long series of one and two-day courses aimed at students and professionals in business, research, and government from 2016-2023. The material is open to anyone. Feel free to use these materials for educational purpose!

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Basics of R for Data Science and Statistics

Course description

This course introduces the powerful and popular R statistical software through the RStudio integrated development environment. R is fully developed programming language and one of the major platforms for doing data science. This course covers frequently used data structures, importing raw data, common data manipulations, summary statistics, and data visualizations through the suite of packages called the tidyverse.

Course Outline

The course provides a modern introduction to the R through the extremely popular suite of packages called the tidyverse. A rough outline is given below:

Day 1:

• Basics of how R stores data
• R packages and the tidyverse
• Reading data from common formats into R (readr package)
• Using R Markdown for reproducibility (rmarkdown and knitr packages)
• Common data manipulations and creating new variables (dplyr package)

Day 2:

• Reshaping data for summarizing and modeling (tidyr package)
• Types of data and numeric summaries (including across groups)
• Creating publication ready graphs (ggplot2 package)

Here is the course site.

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Improving R Programs

Course description

This course introduces common programming techniques that can improve the efficiency of your R programs. These techniques include the use of loops and vectorized functions to avoid repeated sections of code. To really take R programs to the next level, we’ll see how to write custom functions that will help to streamline code.

Course Outline

The course provides a brief overview of R data structures followed by the following topics:

• Loops in R
• Vectorized functions (apply family of functions)
• How R functions work
• Function writing

Here is the course site.

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R for Automating Workflow & Sharing Work

Course description

The course provides participants an introduction to utilizing R for writing reproducible reports and presentations that easily embed R output, using online repositories and version control software for collaboration, creation of basic websites using R, and the development of interactive dashboards and web applets.

Course Outline

Students will learn about the following topics:

• The R Markdown language
• How to automate reports with R Markdown
• Use of git and github for collaboration and version control
• Basic creation of websites through Markdown and github
• R Shiny web apps

Here is the course site.

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