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.
Applied Learning Project
Learners will practice code review, organize their own data analysis projects, share and track their code changes on GitHub using version control, create shareable computing environments using containers and tools like Docker, and automate testing of their code using continuous integration and continuous deployment (CI/CD) tools like GitHub Actions.
