All of our lessons are freely available under the Creative Commons - Attribution License. You may re-use and re-mix the material in any way you wish, without asking permission, provided you cite us as the original source (e.g., provide a link back to this website).
If you have questions about contributing to particular lessons, please contact their maintainers (listed below). If you would like to develop new lessons, please see our lesson incubation process.
|The Unix Shell||Gabriel Devenyi, Ashwin Srinath|
|Version Control with Git||Ivan Gonzalez, Daisie Huang|
|Version Control with Mercurial||Doug Latornell|
|Using Databases and SQL||Abigail Cabunoc Mayes, Sheldon McKay|
|Programming with Python||Trevor Bekolay, Valentina Staneva|
|Programming with R||Daniel Chen, Harriet Dashnow|
|R for Reproducible Scientific Analysis||Thomas Wright, Naupaka Zimmerman|
|Programming with MATLAB||Isabell Kiral-Kornek, Ashwin Srinath|
|Automation and Make||Gerard Capes|
|Instructor Training||Erin Becker, Christina Koch|
You may also enjoy Data Carpentry's lessons, which focus on data organization, cleanup, analysis, and visualization.
To learn more about how our lessons are structured, and why, please see the example lesson.
Video recordings of our lessons are listed below; additions are very welcome.
These lessons have been contributed by community members.
|Testing and Continuous Integration with Python||Katy Huff|
|From Excel to a Database||Greg Wilson|
|Data Management in the Ocean, Weather and Climate Sciences||Damien Irving|
|Controlling a Quadcoptor With Your Mind||Isabell Kiral-Kornek|
|Visualizing Your Data on the Web Using D3||Isabell Kiral-Kornek|
|Working With Data on the Web||Greg Wilson|
|Intermediate/Advanced R Lessons||Scott Ritchie|
|Programming with GAP||Alexander Konovalov|
|Plotting and Programming in Python||Nathan Moore|
Dialogue & Discussion
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