1. Introduction to Setting Up the Python Environment for Data Science and Machine Learning
2. Installing Python: Choosing a Version and Installation
3. Installing and Configuring Anaconda
4. Overview of Jupyter Notebook and its Installation

Jupyter Notebook is an open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It supports various programming languages, including Python, R, and Julia. The primary use of J
5. Installation of necessary libraries: NumPy, Pandas, Matplotlib, Scikit-learn
6. Configuring Virtual Environments Using venv and conda
7. Package Management with pip and conda
8. Setting Up the Development Environment: An Overview of PyCharm and VSCode
9. Checking the installation and testing the environment
10. Conclusion and recommendations for further study