Modules
Overview
To the left, you can find links to all of the course modules. Click one to get started.
Tip
See BruinLearn for the complete course syllabus, including information about course policies, grading, office hours, and more!
Schedule for Spring 2026
| Week | Date | Module | Description |
|---|---|---|---|
| 1 | March 31, April 2 |
Intro to Programming with R | Installation and familiarization with R and RStudio interface; Data organization, reproducible scientific programming |
| 2 | April 7, 9 | Programming Foundations: Part 1 Part 2 |
Variables, vectors, branches, loops, functions |
| 3 | April 14, 16 | Data Summaries | Importing and summarizing data, tidyverse pipes |
| 4 | April 21, 23 | Data Visualization | Exploratory data visualization with ggplot, customizing plots |
| 5 | April 28, 30 | Data Wrangling | Selecting and filtering data, creating new variables |
| 6 | May 5, 7 | Data Tidying | What is “tidy” data and how do we get it |
| 7 | May 12, 14 | Combining datasets; Basic statistical analysis in R, including t-tests and ANOVAs |
|
| 8 | May 19, 21 | Stats, continued + Data Workshop | Statistical analysis of sample datasets; Working with project datasets |
| 9 | May 26, 28 | Intro to Machine Learning | Simple machine learning models for classifying psychological outcomes |
| 10 | June 2, 4 | Review (with code); Project highlights | Final projects due |