🧠 Python Algorithms & Data Structures – Learning Notes

This repository contains my personal learning notes and Jupyter notebooks from following the "Data Structures and Algorithms in Python" course on YouTube:
🎥 Watch the full course here

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📚 Overview

The goal of this repository is to document my journey while learning the fundamentals of algorithms, data structures, and problem-solving in Python.
Each notebook focuses on a specific topic — from simple lists and loops to trees, graphs, and sorting algorithms.

All examples are written and executed in Jupyter Notebooks, combining code, explanations, and visual outputs.

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🧩 Topics Covered

• Python basics refresher (variables, loops, functions)
• Big-O notation and time complexity
• Arrays and linked lists
• Stacks and queues
• Searching algorithms (linear, binary)
• Sorting algorithms (bubble, merge, quick)
• Trees and binary search trees
• Graphs, BFS & DFS
• Recursion and dynamic programming
• Problem-solving practice

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⚙️ Setup Instructions

1. Clone the repository

git clone https://github.com/<your-username>/python-algorithms-learning.git
cd python-algorithms-learning

2. Create a virtual environment (recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Launch Jupyter Notebook

jupyter notebook

Then open any .ipynb file and start exploring.

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🧰 Requirements

• Python 3.10+

• Jupyter Notebook (pip install notebook)

• Optional visualization libraries:

  pip install matplotlib networkx numpy

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🧠 Structure

DSA Python/
│
├── 01_sequences.ipynb
├── 02_lists.ipynb
├── 03_tuples.ipynb
├── 04_sets.ipynb
├── 05_dictionaries.ipynb
├── 06_list_comprehension.ipynb
├── 07_stacks.ipynb
└── README.md

(File names and order may change as the course progresses.)

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🚀 Goals

• Strengthen understanding of algorithmic thinking
• Learn how to analyze and improve code performance
• Practice writing clean, efficient Python code
• Build a personal reference for future projects

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🧩 Resources

• 🎥 YouTube Course – "Data Structures and Algorithms in Python"
• 📘 Python Docs
• 💻 LeetCode — practice problems
• 🧮 Big O Cheat Sheet

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🧑‍💻 Author

Sebastian Falter Learning Data Structures & Algorithms with Python 🐍 📬 GitHub Profile

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🪪 License

This project is open-source and available under the MIT License.