Coding and Cookies

Facts: 

1. Researchers are producing more data than ever before.

2. It's literally impossible to analyze all of these data by hand.

3. Research is really repetitive

4. Automating data processing and analysis will streamline your research

The Coding and Cookies series will teach you the basics of programming in R or Python to make your research more efficient and reproducible. 

Coding & Cookies is offered in collaboration with the Department of Statistics' Graybill Statistics and Data Science Laboratory. At these interactive workshops, we will review key concepts and work through exercises and questions, with individual help available.

Learning materials are publicly available on this guide (see links to the left). If sessions are full, interested students are encouraged to review these materials and get in touch with the instructors for follow-up questions. 

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Spring 2025 schedule:

 

Python Workshops

Python workshops will be held online. Register below to reserve your spot!

• Python 101 - Introduction to Python, February 17, 10:00-11:50am

Registration link for Python 101

• Python 102 - Working With Data, February 24, 10:00-11:50am

Registration link for Python 102

• Python 201 - Data Visualization, March 3, 10:00-11:50am

Registration link for Python 201

• Python - Shareable Jupyter Notebooks with GitHub, March 10, 10:00-11:50am

Registration link for Shareable Jupyter Notebooks with GitHub

• Python - “Bring Your Own Data” Drop-In Session, March 24, 10:00-11:50am

Registration link for Python Drop-In Session

 

R Workshops

R workshops will be held in person at Morgan Library. Register below to reserve your spot!

• R Basics, February 19, 10:00-11:50am

Registration link for R Basics

• Tidy Data in R, February 26, 10:00-11:50am

Registration link for Tidy Data in R

• Data Visualization using ggplot2, March 5, 10:00-11:50am

Registration link for Data Visualization using ggplot2

• Reproducible Reports using RMarkdown, March 12, 10:00-11:50am

Registration link for Reproducible Reports using RMarkdown

• R - “Bring Your Own Data” Drop-In Session, March 26, 10:00-11:50am

Registration link for R Drop-In Session