Enhancing Reproducible Science with GitHub and Docker

This Specialization is intended for scientific researchers who work with data and want to make their analyses yield consistent results regardless of who conducts the analysis or when it is run. The four topic courses and capstone course will teach you best practices, help you practice hands-on skills, and provide templates to help you adapt the content for your own research needs. Students will learn about code review, version control with Git and GitHub, using containers with tools like Docker to keep computing environments consistent, and using continuous integration/deployment tools like GitHub Actions to automatically run and test your code

• Organize analysis files and track code changes with version control
• Automate testing and rerunning of code
• Enable shareable computing environments for consistent results

• No prior deep experience required, basic computer and internet skills sufficient
• Ability to read course materials in English and complete exercises