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An Introduction to Git and GitHub: A Practical Guide for Busy Researchers

About This Project

This book is a practical guide to using Git and GitHub for researchers, originally acting as a reference for the Penn State Center for Infectious Disease Dynamics' short workshop on using Git and GitHub as researchers.

It covers a wide range of topics, from getting started and installing all the necessary software to provide as soft a landing as possible for the first foray into Git and GitHub, to the key concepts and workflows that researchers need to know to use Git and GitHub effectively.

As time goes on, I aim to add more advanced topics, workflows, and solutions to gotchas, so this book can act as a reference for all researchers, regardless of their level of experience with Git and GitHub. That includes myself, as I'm still learning new things about Git and GitHub all the time, and definitely forget things I've learned in the past!

Motivation

There are plenty of great resources out there for learning Git and GitHub. So why write another one?

Well, in part, I wanted to try and consolidate the information out there into a book that doesn't have a bias and focus on R and R-Studio tools, which many of the more introductory resources for researchers do, and without getting too deep into the weeds like some of the resources aimed at software developers rather than busy researchers.

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License

This project is licensed under the MIT License - see the LICENSE file for details

Contact

If you see any errors or have any suggestions, please feel free to open an issue or pull request! If you wish to contact me directly, you can do so at my email address:

arnold {dot} crk {at} gmail {dot} com

Acknowledgements

This book stands on the shoulders of giants, most notably:

All of these, and miscellaneous other resources and blog posts, have been invaluable in my own learning of Git and GitHub, and I hope that this book can be similarly useful to others.

The R code for the simulation is adapted from Ottar Bjornstad's excellent Epidemics: Models and Data using R book (GitHub repo here).