Udemy - Oops In Python

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Free Download Udemy - Oops In Python
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.17 GB | Duration: 4h 43m
Mastering Object-Oriented Programming in Python: From Fundamentals to Advanced Design Patterns

What you'll learnCore 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
RequirementsBasic 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
DescriptionThis 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, parti[beeep]nts 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.
OverviewSection 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.

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