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Tuesday Tip #12: Make your FIRST open source contribution 🏆

Published about 1 year ago • 1 min read

Hi Reader,

Have you been using AI tools (like ChatGPT) to streamline your education or work? If so, hit reply and tell me about your experience! I haven’t used them much, so I’d love to hear from others.

Speaking of AI tools, check out this thought-provoking 6-minute video, in which my friend Ken Jee explains why he’s ALL IN on AI tools.

Anyway, let’s move on to today’s tip!

👉 Tip #12: How to make your first open source contribution

Have you thought about contributing to an open source project, but you’re too confused by the process to even try? I’ve been there too!

There are many good reasons to contribute to open source:

  • It builds your résumé by demonstrating that you can collaborate with others on code.
  • It gives you practice with Git and GitHub, which is a valuable data science skill.
  • It feels good to give back to a project that you use!

However, it’s easy to think that you’re not ready to contribute:

  • Don’t I need to be an excellent coder?
  • Don’t I have to set up a complex development environment?
  • Don’t I need to master Git first?

The answer to these questions is NO! It’s WAY easier than you think to get started:

  1. Pick an open source library that you already use.
  2. Look through its documentation for a typo or broken link to fix. (Making a simple fix allows you to focus on the contribution process.)
  3. Follow my step-by-step guide to contribute your fix. (I’ll show you every button to click and every Git command to write!)
  4. Celebrate learning a new skill AND making that library better for every person who uses it!

Seriously, you could make your first open source contribution TODAY! How great would that feel?!?

Once you’re done, share a link to your pull request so that we can celebrate together! 🎉

Good luck!

If you enjoyed this week’s tip, please forward it to a friend! Takes only a few seconds, and it really helps me out! 🙌

See you next Tuesday!

- Kevin

P.S. No one will remember…

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Learn Data Science from Data School 📊

Kevin Markham

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