About

This course provides students with a foundation in exploring data using the R programming language. Students will learn how to source, manage, transform, and explore a wide variety of data types. Students will also master the fundamental concepts for visualizing and communicating information contained in raw data, building on fundamental principles of human psychology and visual information processing. All analyses will be conducted to support fully reproducible workflows from raw data to results using Quarto and Github. Finally, agentic AI tools such as Claude Code or other similar command line tools will be leveraged to write and audit code that supports all analyses. Teaching will involve interactive lectures with plenty of class time spent working on examples and coding. Students will be assessed through in-class quizzes, weekly homework assignments, and exploratory projects. Throughout the semester, students will work on a research project of their own design to demonstrate mastery of the course’s topics. At the end of the semester, students will submit a final, reproducible report of their project along with a 10-minute video presentation of their findings.

This course was inspired by many other courses / resources that cover similar material. In addition to my own developed material, I have also modified material from other courses and workshops - a full list of sources can be found in the LICENSE page.

This course was originally created by Dr. John Paul Helveston at the George Washington University for the Spring 2020 semester.