This chapter introduces the primary libraries for numerical computing and data analysis in Python: NumPy and Pandas. These tools provide the foundation for many data preparation and manipulation tasks frequently used in data science and artificial intelligence applications.

You will learn what NumPy and Pandas are and understand their significance in typical data workflows. We will guide you through setting up your development environment, including installing the necessary libraries using common package managers like pip or environments like Anaconda. You will execute initial code snippets using these libraries to verify your installation and become familiar with Jupyter Notebooks, a standard tool for interactive data work. The chapter concludes with a practical exercise focused on environment configuration and initial library usage.