Object Oriented Programming in Python

Learn about classes and objects in Python through some interesting analogies
Free tutorial
Rating: 4.2 out of 5 (150 ratings)
16,240 students
1hr 55min of on-demand video

Object Oriented Programming in Python


  • Yes, A Basic knowledge in Python


Hey there! This course will give you deep insights on

1. What are classes in Python and how to define them?

2. What are objects and how are they related and differentiated from classes?

3. What are methods and how are they bundled with objects?

4. How do you define an object by its attributes and methods?

5. The concepts of OOP like Encapsulation, Inheritance, Polymorphism


1. An example of complex numbers in Math has been taken and analysed using OOP

2. The concept of Inheritance is actually explained through two famous movies Interstellar and Inception

and a lot more analogies

Nothing more to write here! I'll see you there in my course!

Object-oriented programming (OOP) is a programming paradigm based on the concept of "objects", which can contain data and code: data in the form of fields (often known as attributes or properties), and code, in the form of procedures (often known as methods).

A feature of objects is that an object's own procedures can access and often modify the data fields of itself (objects have a notion of this or self). In OOP, computer programs are designed by making them out of objects that interact with one another.[ OOP languages are diverse, but the most popular ones are class-based, meaning that objects are instances of classes, which also determine their types.

Who this course is for:

  • Beginner Python Programmers


Engineer | Course Instructor
Sujithkumar MA
  • 4.3 Instructor Rating
  • 4,129 Reviews
  • 208,727 Students
  • 33 Courses

Languages - C, C++, Python, Verilog, System Verilog

Hardware - Digital Logic Design, Computer Architecture, VLSI Design, Analog Electronics, Signal Processing, Embedded Systems

Software - Data Structures & Algorithms, Operating Systems, Database Management Systems,  Computer Networks, Machine Learning, Deep Learning.

Tools - Xilinx Vivado, Matlab, Multisim, Altium, Arduino IDE, TinkerCAD, Tanner EDA, Cadence Virtuoso

Boards - Arduino, 8051, TIVA, Raspberry Pi, NodeMCU

Areas of Interest - Artificial Intelligence, Digital Design, Software Engineering, Algorithms

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