Python Classes & Data Encapsulation: Private, Protected, and Public Scopes

In this lecture for the Programming for Artificial Intelligence series, we dive into the core of Object-Oriented Programming (OOP) in Python: Classes. Understanding how to structure data and behavior is essential for building scalable AI systems. We move beyond basic syntax to explore how Python handles data visibility and internal state. Key Topics Covered: Class Definition: How to properly structure a Python class and initialize objects. Data Members & Member Functions: Defining attributes and methods to represent real-world entities. Access Specifiers: * Public: Default access for all members. Protected (_): The "internal use" convention for subclasses. Private (__): Using name mangling to restrict access and protect data integrity. Encapsulation: Why controlling access to data members is a best practice in software engineering. This session is designed to give you the structural foundation needed before we move into more complex AI design patterns and library implementations. Python OOP, Python Classes, Programming for AI, Data Members, Member Functions, Private vs Protected Python, Name Mangling, Python Encapsulation, University of Central Punjab, Python Tutorial for AI, Software Design Patterns, Access Modifiers Python.