Oops In Python

Mastering Object-Oriented Programming in Python: From Fundamentals to Advanced Design Patterns

What you'll learn

Core OOP Concepts: Classes, Objects, Methods

Inheritance: Create class hierarchies

Polymorphism: Implement flexible behaviors

Encapsulation & Abstraction: Hide details

Magic Methods: Customize class operations

Multiple Inheritance: Use complex class structures

Design Patterns: Clean and maintainable code

Dynamic Classes: Modify classes at runtime

Real-World Projects: Practical OOP applications

Debug & Optimize: Improve performance and code

Requirements

Basic Python Programming Knowledge

Understanding of Data Types & Variables

Familiarity with Functions and Loops

Experience with Python Syntax and IDEs

Problem-Solving and Logical Thinking

Basic Knowledge of File Handling in Python

Willingness to Learn OOP Concepts

Access to a Computer with Python Installed

Description

This course is designed to provide a comprehensive understanding of Object-Oriented Programming (OOP) in Python, focusing on building efficient, scalable, and reusable software components. It covers fundamental concepts such as classes, objects, inheritance, polymorphism, encapsulation, and abstraction, while also exploring advanced topics like magic methods, multiple inheritance, and dynamic class modifications.Throughout the course, participants will start by learning the basics of OOP and progress to more complex aspects, including the implementation of design patterns that promote code modularity and maintainability. Each module includes hands-on coding exercises and real-world projects to reinforce key concepts, ensuring that learners can apply their knowledge in practical scenarios. Additionally, the course emphasizes best practices for structuring OOP code, debugging techniques, and performance optimization.By the end of the program, students will have mastered the skills needed to develop complex applications and implement sophisticated OOP designs in Python. The curriculum is designed for both beginners who want to build a strong foundation in Python programming and experienced developers looking to enhance their understanding of software architecture. Upon completion, learners will have the confidence to apply OOP principles in a variety of software development environments, making this course ideal for anyone aiming to elevate their Python programming skills and pursue roles in software engineering or design.With a focus on practical learning and real-world applications, this course is the perfect stepping stone for mastering OOP in Python and building a solid foundation for future software development projects.

Overview

Section 1: Advance Python (OOP)

Lecture 1 Introduction to Object Oriented Programming (OOP) in Python

Lecture 2 Class vs Object in OOP

Lecture 3 Writing our first Class in OOP

Lecture 4 Methods vs Functions

Lecture 5 Class Diagram in OOP

Lecture 6 Magic Methods/Dunder Methods in OOP

Lecture 7 Concept of self in OOP

Lecture 8 How object access attributes in OOP

Lecture 9 Reference Variable in OOP

Lecture 10 Pass by reference in OOP

Lecture 11 Mutibility of Object in OOP

Lecture 12 What is instance variable in OOP

Lecture 13 Encapsulation in OOP

Lecture 14 getter & setter methods in OOP

Lecture 15 Collection of class objects in OOP

Lecture 16 Static Variables & Methods in OOP

Lecture 17 Aggregation in OOP

Lecture 18 Aggregation class diagram in OOP

Lecture 19 Inheritance in OOP

Lecture 20 Inheritance class diagram in OOP

Lecture 21 What gets Inherited

Lecture 22 Method Overriding in OOP

Lecture 23 Super Keyword in OOP

Lecture 24 Types of Inheritance in OOP

Lecture 25 Polymorphism in OOP

Lecture 26 Abstraction in OOP

Section 2: Moduler Coding in Python

Lecture 27 Moduler Coding in Python

Lecture 28 if __name__ == "__main__" in Python

Section 3: Mega OOP Project

Lecture 29 Mega OOP Project

Lecture 30 Conclusion & Future Advice

Beginner Python Programmers seeking to learn OOP concepts.,Experienced Developers wanting to deepen OOP skills.,Students looking to enhance their programming foundations.,Software Engineers aiming to improve code modularity.,Data Scientists wanting to build reusable data models.,Tech Enthusiasts interested in software design principles.,Freelancers needing to write scalable applications.,Career Switchers exploring software development roles.