Lesson Materials
Click one of the categories below to review the lesson materials for the workshops we teach. Many of the lessons listed are taught as part of our regularly offered Software Carpentry (SWC) and Data Carpentry (DC) workshops. Others are taught as standalone workshops. Look for the code (SWC, DC, or no code for standalone workshops) listed next to each lesson to determine which workshop the lesson belongs to.
In addition, the Data Carpentry workshop has several variants which have been customized to suit the needs of specific research topics (ecology, genomics, geospatial, and social sciences). Find all variants of each lesson listed in square brackets next to the lesson names.
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Data Analysis & Visualization
Cloud Computing
- Intro to Cloud Computing in AWS (DC) [Genomics]
Python
R/RStudio
- Intro to R and RStudio (DC) [Ecology, Genomics, Geospatial, Social Sciences]
- R for Raster and Vector Data (DC) [Geospatial]
- Data Science for Clinicians and Docs
Unix
- Automating Tasks with the Unix Shell (DC – Genomics, SWC)
- Automation with Make
Data Cleaning & Management
- Data Cleaning with OpenRefine (DC) [Ecology, Social Sciences]
- Data Management with SQL (DC) [Ecology, Social Sciences]
- Data Organization in Spreadsheets (DC) [Ecology, Social Sciences]
- Data Wrangling and Processing (DC) [Genomics]
- Project Organization and Management (DC) [Genomics]
Machine Learning & AI
We maintain a library of our machine learning & AI workshops on the ML+X Nexus platform
Version Control & Containerization
Miscellaneous
Past Workshops
Our previous workshops include Data Carpentry, Software Carpentry, and many others. Data Carpentry is designed to teach data organization and analysis using data that looks familiar to researchers. Software Carpentry is designed for people who are learning to code to develop software or learn best practices in software development. The “Other Workshops” tab features all other workshops, which cover a broad range of topics, including machine learning, docker, data visualization, and more.
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Data Carpentry
August 5-9, 12-13, 2024 – Genomics
June 17-20, 2024 – REU/Undergrad Researchers
June 3-6, 2024 – Geospatial
January 8-11, 2024 – Ecology
August 14-17, 21-22, 2023 – Genomics
June 5-8, 2023 – Geospatial
June 5-8, 2023 – REU/Undergraduates
May 15-18, 2023 – Health Science
January 9-12, 2023 – Ecology
August 22-23, 2022 – Social Science
August 17-18, 2022 – Geospatial
August 1-4, 8-9, 2022 – Genomics
June 6-9, 2022 – REU/Undergraduates
May 16-17, 2022 – Health Science
March 14-17, 2022 – Ecology
August 23-September 3, 2021 – Genomics
July 6-16, 2021 – Geospatial
June 7-14, 2021 – REU/Undergraduates
May 12-19, 2021 – Social Science
May 3-10, 2021 – Health Science
January 18-25, 2021 – Ecology
July 13-17 — Geospatial
June 16-25 — Health Science
June 11-19 — REU / Undergraduates
September 11-October 9, 2019 – Ecology
August 5-6, 12, 2019 – Genomics
July 11-12, 2019 – Geospatial
June 27-28, 2019 – REU / Undergraduates
June 11-12, 2019 – Health Science
January 16-17, 2019 – Ecology
August 27-28, 2018 – Ecology
June 4-5, 2018 – Ecology
January 8-9, 2018 – Ecology
August 22-23, 2017 – Ecology
June 19-20, 2017 – Ecology
January 10-11, 2017 – Ecology
August 23-24, 2016 – Ecology
June 1-2, 2016 – Ecology
January 11-12, 2016 – Ecology
Software Carpentry
January 13-16, 2025
June 24-27, 2024 – REU/Undergraduates
January 16-19, 2024
June 12-15, 2023 – REU/Undergraduates
January 17-20, 2023
June 13-16, 2022 – REU/Undergraduates
January 10-21, 2022
August 9-18, 2021
June 8-17, 2021 — REU / Undergraduates
January 4-13, 2021
August 17-26, 2020
June 10-18, 2020 — REU / Undergraduates
January 22-23, 2020 (included Reproducible Research: Tools and Applications)
September 11-Oct.9, 2019
June 13-14, 2019
January 14-15, 2019
August 29-30, 2018
June 6-7, 2018
January 10-11, 2018
August 30-31, 2017
June 28-29, 2017
January 12-13, 2017
August 29-30, 2016
June 8-9, 2016
January 14-15, 2016
August 26-27, 2015
Other Workshops
December 16-18, 2024 – Trustworthy AI
September 25-November 21, 2024 – Fall Mini-Workshop Series
- git/GitLab
- Intro to Docker
- Interactive Data Visualizations in Python and Streamlit
- Intro to Machine Learning
May 29-31, 2024 – Intro to Deep Learning with Keras
April 15-17, 2024 – Text Analysis Workshop
September 13-December 20, 2023 – Fall Mini-Workshop Series
- Unix Shell
- Intro to Machine Learning
- git/GitLab
- Intro to Docker
- CHTC
- Interactive Data Visualizations in Python and Streamlit
- The Basics of Data Visualization
August 14-16, 2023 – High Dimensional Data Analysis
May 31-June 2, 2023 – Introduction to Deep Learning
March 13-17, 2023 – Intermediate Research Software Development in Python
October 24-25, 2022 – Building Transformer-Based Natural Language Processing Applications
September 7-December 14, 2022 – Fall Mini-Workshop Series
- Unix Shell
- Git/GitHub
- Intro to Machine Learning with Sklearn
- Intro to Docker
- Interactive Data Visualizations in Python
- Intro to Julia
April 21-April 22, 2022 – Introduction to Deep Learning
September 15-December 8, 2021 – Fall Mini-Workshop Series
- Data Science for Clinicians and Docs
- Intro to Docker
- Git/GitHub
- Intro to Machine Learning with SKLearn
- Interactive Data Visualizations in Python
January 29-April 29, 2020 – Spring Mini-Workshop Series
- Automating Tasks with Unix Shell
- Introduction to Data
- Introduction to SQL
- Introduction to Git/GitHub
- Introduction to GitHub Pages
- Introduction to Docker
- Automation with Make
September 16-December 9 , 2020 – Fall Mini-Workshop Series
- Automating Tasks with Unix Shell
- Data Management with SQL
- Version Control with Git/GitHub
- Jekyll Pages
- Introduction to Docker
History
Since January 2019, the Data Science Hub has been carrying on the tradition of hosting these workshops on the UW-Madison campus that the Advanced Computing Initiative started in April 2013. Research Computing Facilitators from the Center for High Throughput Computing have also been key in developing the Carpentries community at UW-Madison.