This repository contains a collection of Python tutorials in the form of Jupyter Notebooks. These tutorials cover the basics of Python, Object-Oriented Programming, and scientific computing with NumPy.

1. 000-about_py.ipynb: Introduction to Python, its features, and setting up the environment.
2. 001-python_by_example.ipynb: Learning Python through example programs.
3. 002-python_essentials.ipynb: Essential Python concepts including data types and control flow.
4. 003-oop_intro.ipynb: Introduction to Object-Oriented Programming (OOP) in Python.
5. 004-numpy.ipynb: Introduction to NumPy for array processing and numerical computing.
6. 005-pandas_intro.ipynb: Introduction to Pandas for data manipulation and analysis.
7. 006-visualization_matplotlib_seaborn.ipynb: Data Visualization with Matplotlib and Seaborn.
8. 007-scikit_learn_intro.ipynb: Machine Learning basics with Scikit-Learn.
9. 008-modern_python_features.ipynb: Modern Python features (f-strings, type hints, etc.).
10. 009-coding_with_llms.ipynb: How to code effectively with LLM tools.
11. UC-getting_started.ipynb: Guide to setting up the Python environment (Anaconda, Jupyter).
12. UC-builtin_functions.ipynb: Overview of Python's built-in functions.

• Python 3.x
• pip

1. Clone the repository:

   git clone <repository-url>
   cd Python-tutorial

2. Create a virtual environment:

   python3 -m venv .venv
   source .venv/bin/activate  # On Windows use `.venv\Scripts\activate`

3. Install the required dependencies:

   pip install -r requirements.txt

Start the Jupyter Server:

jupyter notebook

This will open the Jupyter interface in your browser, where you can select and run the notebooks.

This project is licensed under the MIT License - see the LICENSE file for details.