1. licenses-copyright-wrapup.html
Reproducible and Trustworthy Workflows for Data Science
  • Welcome
  • intro.html
    • 1  How do reproducible and trustworthy workflows impact data science?
    • 2  Introduction to the Bash Shell
  • version-control.html
    • 3  SSH for authentication
    • 4  Version control (for transparency and collaboration) I
    • 5  Version control (for transparency and collaboration) II
    • 6  Project management using GitHub
  • projects-envs-containers.html
    • 7  Filenames and data science project organization, Integrated development environments
    • 8  Conda lock: reproducible lock files for conda environments
    • 9  Virtual environments
    • 10  Introduction to containerization
    • 11  Using and running containers
    • 12  Customizing and building containers
  • data-testing.html
    • 13  Data validation
    • 14  Introduction to testing code for data science
  • automation.html
    • 15  Non-interactive scripts
    • 16  Reproducible reports
    • 17  Data analysis pipelines with scripts
    • 18  Data analysis pipelines with GNU Make
  • packaging-ci-cd-publish.html
    • 19  Packaging and documenting code
    • 20  Automated testing and continuous integration
    • 21  Deploying and publishing packages
  • licenses-copyright-wrapup.html
    • 22  Copyright and licenses
    • 23  Workflows for reproducibile and trustworthy data science wrap-up
  • appendix.html
    • 24  Defining functions in Python
    • 25  Defining functions in R
    • 26  Reproducible reports
21  Deploying and publishing packages
22  Copyright and licenses