Data Science RoadMap

🧭 Your Complete Data Science Roadmap (Beginner → Pro)

Hey everyone 👋,

If you’ve ever wondered “Where do I start learning Data Science?”, you’re not alone. Data Science is one of the most in-demand fields today, but the overwhelming amount of resources often confuses beginners.

That’s why I created a complete roadmap to guide you step by step.

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🔹 Topics Covered

Here’s a quick overview of what you’ll learn in the roadmap:

1. Mathematics for Data Science (Linear Algebra, Probability, Statistics)
2. Programming (Python) – Numpy, Pandas, Matplotlib, Seaborn
3. Data Preprocessing & Cleaning
4. Exploratory Data Analysis (EDA)
5. Machine Learning Algorithms – Supervised & Unsupervised
6. Deep Learning Basics – Neural Networks, TensorFlow/PyTorch
7. Projects & Case Studies
8. Deployment & Real-world Applications

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🔹 GitHub Repository

I’ve compiled everything neatly into a GitHub repository.

👉 Check it out here: Data Science Roadmap Repo
👉 Check it out Live Demo: Live Page

You’ll find:

• Learning resources 📚
• Code examples 💻
• Suggested projects 🚀
• Useful links & articles 🔗

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🔹 Why I Built This

When I started learning Data Science, I often got lost between random tutorials and courses. To save others from the same struggle, I decided to document a clear path and make it open-source for everyone.

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🔹 How You Can Use This Roadmap

• Follow it step by step if you’re a beginner.
• Use it as a checklist if you’re already learning.
• Contribute by suggesting improvements (open for PRs 🙌).

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💬 Final Thoughts

If you’re serious about becoming a Data Scientist, start today. Don’t wait for the “perfect resource” – instead, follow a roadmap and keep building projects along the way.

👉 Repo link again: Data Science Roadmap

I hope this helps you kickstart your journey 🚀

Let me know your thoughts, and feel free to contribute to the repo.

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✍️ Written by Akshit Suthar