Cheat Sheet for Your First Open Source Contribution

Surya prakash Sharma — Sun, 11 Oct 2026 02:24:56 +0000

Making your first open source contribution is intimidating. Honestly, it’s rarely the code that holds people back—it’s usually the fear of messing up a Git command, doing something wrong in the GitHub UI, and looking foolish in front of maintainers.

I spent way too much time staring at my terminal the first time I tried to contribute, terrified I was going to accidentally overwrite a master branch somewhere.

To save you that headache, I put together a visual cheat sheet that walks through the exact process from start to finish. No fluff, just the actual steps you need to take to get your first Pull Request merged.

What's in the deck:-

1) The GitHub UI workflow:- Exactly where to click to fork a repo and open a PR, without getting lost in the interface.
2) Copy-paste VS Code commands:- The exact Git commands you need for your terminal to clone, branch, commit, and push safely.
3) Unwritten rules:- Quick notes on formatting commit messages and PR descriptions so maintainers actually want to look at your code.

The Workflow:-

If you just need a quick refresher of the lifecycle, it always follows this loop:
Fork on GitHub -> Clone to VS Code -> Create a new branch -> Write code -> Commit & Push -> Open a PR.

The slides below break down the "how" for every single one of those steps.

suryaprkash778-dot / open-source-cheat-sheet

open source cheat sheet

open-source-cheat-sheet

open source cheat sheet

View on GitHub

If you use this to make your first contribution this week, drop a link to your PR in the comments. I'd love to see what you're working on.

Data Science, ML, and Why I'm Learning in Public 🚀

Surya prakash Sharma — Tue, 30 Dec 2025 13:12:12 +0000

Let’s be real—the AI world is moving so fast right now that if you blink, you’ve missed three new frameworks and a dozen research papers. 😅

I’m currently at UPES, Dehradun, diving head-first into the world of Data Science and Machine Learning. I’m not just here to stare at math on a whiteboard; I’m obsessed with taking that theory and building stuff that actually solves things. 🛠️

The Focus 📊 Right now, I’m all in on mastering ML architectures and making sense of messy data. I’m a big believer that the best engineers are the ones who can bridge the gap between "cool idea" and "working code." That’s the goal.

The Global Side 🌍 Beyond the technical side, I’ve kept my focus global. I’m fluent in English, Hindi, and German. 🇩🇪🇮🇳 Having German in my toolkit is a huge plus for me, especially with the massive AI and Automotive R&D happening in Europe. It’s about being able to collaborate across borders without a translator getting in the way.

Why I’m blogging ✍️ I'm using this space as my "digital lab notebook." I’ll be sharing:

🤖 Deep dives into ML frameworks (simplified, no fluff).

📈 My take on new Data Science tools.

💻 Honest logs of what I'm building—bugs, wins, and everything in between.

I’m always down to connect with industry pros, fellow students, or anyone who’s as hyped about AI . If you’ve got advice for someone hungry for an internship or just want to nerd out about algorithms, hit me up in the comments! 👇🔥

DEV Community: Surya prakash Sharma

Cheat Sheet for Your First Open Source Contribution

What's in the deck:-

The Workflow:-

suryaprkash778-dot / open-source-cheat-sheet

open source cheat sheet

open-source-cheat-sheet

Data Science, ML, and Why I'm Learning in Public 🚀