CDSI offers a series of workshops on topics related to programming languages, data science, advanced statistical methods, cluster computing, machine learning and more. The workshops are offered for free to the entire McGill community (students, researchers, and staff) from all faculties.
Workshops take place in hybrid format (in person and online). Registration closes 24 hours before the workshop.
If you need to cancel your registration, follow the link provided on your registration confirmation email or cdsi.science [at] mcgill.ca (email us) as soon as possible in order to give your seat to another participant.
Students who take our workshops may be eligible for the Student Experience Record (SER). In order to be eligible for SER, students must attend at least 70% of the workshops in a given workshop series as listed below. For more information, please cdsi.science [at] mcgill.ca (email us).
Fall 2026 Workshop Schedule
Introduction to Data Science with R Series
Students must complete at least 4 out of the 5 workshops in this series for SER recognition.
| Workshop | Date | Time | Registration Link |
|---|---|---|---|
| Introduction to R in Rstudio | Tuesday, September 15, 2026 | 10:30 AM to 12:30 PM | Register |
| Data Science Life Cycle in R | Tuesday, September 22, 2026 | 10:30 AM to 12:30 PM | Register |
| Programming with Gen. AI in R | Friday, September 25, 2026 | 10:30 AM to 12:30 PM | Register |
| Data Wrangling in R | Tuesday, September 29, 2026 | 10:30 AM to 12:30 PM | Register |
| Introduction to Data Visualization in R | Tuesday, October 6, 2026 | 10:30 AM to 12:30 PM | Register |
Intermediate Data Science in R Series
Students must complete at least 4 out of the 6 workshops in this series for SER recognition.
| Workshop | Date | Time | Registration Link |
|---|---|---|---|
| Data Visualization in R, Intermediate | Tuesday, October 20, 2026 | 10:30 AM to 12:30 PM | Register |
| Building Interactive Plots in R | Tuesday, October 27, 2026 | 10:30 AM to 12:30 PM | Register |
| Acquiring Data from the Internet in R | Tuesday, November 3, 2026 | 10:30 AM to 12:30 PM | Register |
| Creating a Shiny Dashboard in R | Tuesday, November 10, 2026 | 10:30 AM to 12:30 PM | Register |
| Working with Text in R | Tuesday, November 17, 2026 | 10:30 AM to 12:30 PM | Register |
| Introduction to PostGreSQL | Tuesday, November 24, 2026 | 10:30 AM to 12:30 PM | Register |
Introduction to Data Science in Python Series
Students must complete at least 3 out of the 4 workshops in this series for SER recognition.
| Workshop | Date | Time | Registration Link |
|---|---|---|---|
| Data Science Life Cycle in Python | Wednesday, October 21, 2026 | 10:30 AM to 12:30 PM | Register |
| Data Wrangling in Python | Wednesday, October 28, 2026 | 10:30 AM to 12:30 PM | Register |
| Introduction to Data Visualization in Python | Wednesday, November 4, 2026 | 10:30 AM to 12:30 PM | Register |
| Exploratory Data Analysis in Python | Wednesday, November 11, 2026 | 10:30 AM to 12:30 PM | Register |
Foundations of Computing Series
Students must complete all workshops in this series for SER recognition.
| Workshop | Date | Time | Registration Link |
|---|---|---|---|
| Understanding File Systems | Wednesday, September 16, 2026 | 10:30 AM to 12:30 PM | Register |
| Introduction to Linux | Wednesday, September 23, 2026 | 10:30 AM to 12:30 PM | Register |
| Introduction to Cluster Computing | Wednesday, September 30, 2026 | 10:30 AM to 12:30 PM | Register |
Causal Inference Series
Students must complete all workshops in this series for SER recognition.
| Workshop | Date | Time | Registration Link |
|---|---|---|---|
| Causal Inference 1 | Friday, October 2, 2026 | 10:30 AM to 12:30 PM | Register |
| Causal Inference 2 | Friday, October 16, 2026 | 10:30 AM to 12:30 PM | Register |
| Causal Inference 3 | Friday, October 23, 2026 | 10:30 AM to 12:30 PM | Register |
Become a CDSI Learning Assistant
Interested in supporting CDSI workshops and summer camps while gaining valuable teaching and leadership experience? CDSI hires McGill undergraduate students as Learning Assistants to help instructors, answer participant questions, and support hands-on learning activities.
If you have experience in programming, data science, machine learning, computer systems, statistics, or related fields, complete the form below to express your interest. Eligible candidates will be contacted when Learning Assistant opportunities become available.