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📘 README.md

CoC Python Workshop

Welcome to the CoC Python Workshop repository! 🚀

This repository is designed to help students practice Python after learning the fundamentals, through tutorials, hands-on exercises, and debugging challenges.

📂 Repository Structure

🔹 tutorials/ — Learn & Explore

This is your primary learning directory. Use it to understand Python concepts and explore its power.

It is organized into:

  • fundamentals/ Learn Python basics such as variables, loops, functions, and data types.

  • additional_libs/ Get introduced to commonly used standard and third-party Python libraries.

  • data_science/ Dive into BIG DATA & Data Science concepts, including data handling and analysis.

  • miscellaneous/ Experiment with powerful and fun Python libraries beyond the basics.

🔹 test_playground/ — Practice by Fixing Bugs 🧠

This directory helps you learn by doing.

It contains folders such as:

  • basics/ Contains simple bugs covering standard Python, with no module required

  • intermediate/ Covers slightly more intermediate concepts still nearing fundamentals but with some standard libraries

  • advanced/ Covers codes related to data science, with now fixes and improvements requiring proper understanding and critical thinking.

  • miscellaneous/ Covers random extra topics. Difficulty is mix of intermediate and advanced.

-assets/ Contains some datasets and files used by the buggy codes in the above four folders. Also contains a script that was used to generate them.

📌 These files are mostly correct, but include small bugs or logical errors. 💡 Hints are provided to guide you—try fixing the issues on your own!

📓 Google Colab Walkthrough

A Google Colab Notebook is provided in the main directory for a quick walkthrough of major Python concepts:

👉 Open Colab Notebook

Use this as:

  1. A quick revision guide

  2. A reference while solving exercises

🎯 Goal of This Repository

  1. Strengthen Python fundamentals

  2. Learn debugging and problem-solving

  3. Explore real-world Python libraries

  4. Build confidence through practice

  5. Learn format of contribution in open source and work with PRs and issues.

✨ Have fun learning Python!