profile

Learn Data Science from Data School 📊

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…

Did someone awesome forward you this email? Sign up here to receive data science tips every week!

Learn Data Science from Data School 📊

Kevin Markham

Join 25,000+ aspiring Data Scientists and receive Python & Data Science tips every Tuesday!

Read more from Learn Data Science from Data School 📊

Hi Reader, happy Tuesday! My recent tips have been rather lengthy, so I'm going to mix it up with some shorter tips (like today's). Let me know what you think! 💬 🔗 Link of the week A stealth attack came close to compromising the world's computers (The Economist) If you haven't heard about the recent "xz Utils backdoor", it's an absolutely fascinating/terrifying story! In short, a hacker (or team of hackers) spent years gaining the trust of an open-source project by making helpful...

13 days ago • 1 min read

Hi Reader, Today's tip is drawn directly from my upcoming course, Master Machine Learning with scikit-learn. You can read the tip below or watch it as a video! If you're interested in receiving more free lessons from the course (which won't be included in Tuesday Tips), you can join the waitlist by clicking here: Yes, I want more free lessons! 👉 Tip #43: Should you discretize continuous features for Machine Learning? Let's say that you're working on a supervised Machine Learning problem, and...

20 days ago • 2 min read

Hi Reader, I'm so excited to share this week's tip with you! It has been in my head for months, but I finally put it in writing ✍️ It's longer than usual, so if you prefer, you can read it as a blog post instead: Jupyter & IPython terminology explained 🔗 Link of the week Python Problem-Solving Bootcamp (April 1-21) Want to improve your Python skills quickly? There's no better way than solving problems, reviewing alternative solutions, and exchanging ideas with others. That's the idea behind...

about 1 month ago • 3 min read
Share this post