Add comprehensive setup instructions and scripts for running Jupyter notebooks

[Copilot]

Problem

The repository contained Jupyter notebooks for Python learning but lacked clear instructions on how to run them. Users encountering the repository would find:

• No setup instructions in the main README
• A requirements.txt file with an invalid sqlite3 dependency (causing installation failures)
• No guidance on which notebook to start with or the recommended learning path
• No easy setup options for different environments

Solution

This PR transforms the repository into a user-friendly learning environment by adding comprehensive setup documentation and automated setup scripts.

Key Changes

📚 Enhanced Documentation

• Completely rewrote the main README.md with step-by-step setup instructions
• Added 4 different setup options: Local installation, GitHub Codespaces, Dev Container, and Google Colab
• Created a learning path guide showing the recommended notebook sequence
• Added troubleshooting section for common issues

🛠️ Automated Setup Scripts

• setup.py - Python script with user-friendly output, error handling, and Python version checking
• setup.sh - Shell script alternative for Linux/Mac users
• Both scripts provide helpful fallback instructions when issues occur

🔧 Fixed Dependencies

• Removed sqlite3 from requirements.txt (it's part of Python's standard library and was causing installation failures)
• All other scientific computing dependencies preserved

📖 Course Navigation

• Enhanced course/README.md with quick start guide and notebook descriptions
• Clear learning progression starting with Data.ipynb for Python fundamentals

🐳 Improved Dev Container

• Added helpful comments in .devcontainer/devcontainer.json with post-setup instructions

Usage Examples

Quick automated setup:

python setup.py
# or
./setup.sh

Manual setup:

pip install -r requirements.txt
jupyter notebook

For beginners:

1. Start with course/Data.ipynb for Python fundamentals
2. Progress through Pandas basics and exercises
3. Finish with data visualization techniques

This PR ensures that anyone can easily get started with the Python course materials, regardless of their technical background or preferred development environment.

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