This is a sandbox repository designed to help you practice Git collaboration skills while working with Python and Data Science content. The repository contains a collection of quizzes written by contributors who are participating in the sandbox. As you contribute your own quiz questions, you'll learn essential version control techniques that data scientists use every day!
By asking sandbox participants to submit a quiz (instead of code) the focus of this sandbox and workshops utilizing this sandbox can better focus on the mechanics of Git and GitHub without getting stuck on issues intrinsic to coding (but only tangential to Git). Writing simple plain text quiz questions is lightweight, approachable, and less intimidating than contributing full code modules.
However writing and submitting a quiz in plain text does require creating, editing, and managing files — - - Essentially the same workflows many will often follow in a professional development project. This simplified approach to learning and practicing Git helps participants practice branching, committing, merging, and resolving conflicts in a way that emphasizes the Git collaboration skills rather than programming knowledge.
In other words, other learning experiences can focus on pgramming knowledge. The quizzes in this sandbox serves as a safe stand-in for code, giving everyone a chance to learn how to work together in Git and GitHub while keeping the content fun, accessible, and directly relevant to data science topics.
Git is an essential skill for modern data scientists and programmers:
- Collaboration: Work seamlessly with teammates on shared code
- Team Transparency: See who made what changes and when, improving accountability
- Reproducibility: Keep clear records of changes so your analyses and models can be replicated later
- Version Control: Track changes and maintain a history of your work
- Error Recovery: The version control supports rolling back to earlier versions when mistakes happen or code breaks
- Portfolio Building: Show potential employers you understand professional workflows
- Open Source: Participate in the vibrant data science community
- Scalability: Manage projects from small scripts to enterprise-level software with the same tool
- GitHub For Beginners Video Series - This video will help you be more confident in installing, configuring, and gettings started with Git.
- UW Data Science Hub Intro, Config, Creating a Repo - Version Control with Git
This repository serves as a safe playground where you can:
- Fork this repository to your own GitHub account
- Clone your fork to work on it locally
- Create a Python quiz file with questions suitable for any level of learning
- Commit your changes to your local repository
- Push to GitHub (your clone)
- Submit a Pull Request back to this main repository
Don't worry if you're new to these ideas and these approaches! There is also a beginner-friendly guide to walk you through each step.
Follow the detailed instructions in the Git Fork, Commit, and Contribution Guide to submit your own quiz questions.
You'll be creating multiple-choice quiz questions about Python, data science concepts, or data visualization. This helps you practice Git while reinforcing your knowledge of data science topics!
Don't overthink it. Happy coding and Git collaborating! 💻✨😄