
Explore how classes define blueprints for objects in Python, using attributes, methods, and the __init__ constructor to create reusable, scalable code through instantiation.
Apply inheritance by modeling a base device and a smartphone, then extend to a pro smartphone with a stylus, showcasing multi-level inheritance and code reuse.
Explore encapsulation and abstraction in Python through a coffee-order class that hides internal calculations behind private methods and offers a safe public interface to get price.
Explore polymorphism in Python with a vehicle example where car, train, and aeroplane override accelerate, and learn method overloading via default arguments, highlighting cleaner, scalable, multi-type code.
Explore solid principles and learn the single responsibility principle by separating vehicle, formatting, and insurance logic into dedicated classes for cleaner, more extensible, and testable code.
Explore the open closed principle by transforming a vehicle class into an abstract base with car and truck subclasses, and refactor insurance cost calculation to extend without modifying code.
Learn how the Liskov substitution principle ensures that every subclass can replace its base class without breaking behavior, by implementing all base methods consistently and avoiding runtime exceptions.
Discover the interface segregation principle in SOLID, splitting large interfaces into smaller, relevant ones so cars, trucks, and electric cars implement only refuel or recharge as needed.
Learn how dependency inversion principle promotes depending on abstractions instead of concrete classes, and injects dependencies like brake inspection tool or tire rotation tool to keep open-closed principle intact.
Explore the singleton pattern by implementing a single controlTower instance to coordinate all flights, using a class variable instance and a customized new method to ensure only one object exists.
Learn the builder pattern through a house example, replacing bloated constructors with stepwise, readable methods to set bedrooms, bathrooms, garden, garage, pool, solar panels, and smart home.
Explore the builder pattern, highlighting step-by-step construction, readability, and separation of concerns, with real estate, game development, travel booking, and report generation use cases.
Discover how the strategy design pattern manages multiple algorithms at runtime, from payment options to real-world applications, avoiding monolithic code, with a Python example.
Implement the strategy pattern to refactor a payment processor into separate payment classes, enabling set strategy usage and pay method execution while upholding open-closed and single-responsibility principles.
Apply the strategy pattern to real-life cases like payment gateways with multiple methods, dynamic sorting among bubble sort, quick sort, and merge sort, and authentication using username, password, OAuth, or biometrics.
The adapter design pattern bridges mismatched systems, letting a USB-A plug work with a USB-C port and enabling two incompatible components to collaborate seamlessly.
The adapter pattern wraps the bankService's makePayment to the paymentService interface's pay, via bankServiceAdapter, allowing legacy code to work without changing the original bankService class.
Explore the adapter pattern’s reusability, flexibility, and non-invasive integration for APIs, legacy code, and UI components, while weighing added complexity and overhead.
Explore the state design pattern with a vending machine analogy, showing idle, coin inserted, and dispensing snack states guiding behavior. Encapsulate each state in its class for cleaner, modular code.
demonstrates implementing the state pattern to manage a vending machine, delegating actions to idle, has money, and out of stock states for modular, readable, and scalable code.
Discover how the state design pattern yields cleaner code by encapsulating each state's behavior, enhances extensibility, and enforces separation of concerns, with media players, ATMs, and checkouts as examples.
Master Object-Oriented Programming & SOLID Principles in Python
This course is designed to help you build a strong foundation in Object-Oriented Programming (OOP) using Python, along with mastering SOLID principles to write clean, maintainable, and scalable code. Whether you are a beginner or an experienced developer looking to refine your skills, this course will guide you through practical examples and real-world scenarios.
What You Will Learn:
Core OOP concepts such as classes, objects, inheritance, polymorphism, encapsulation, and abstraction
Understanding and applying SOLID principles for better software design
Writing reusable and modular code using best practices
Real-world coding exercises to reinforce key concepts
Debugging and refactoring techniques to improve code quality
How to structure Python applications following industry standards
Who Should Take This Course?
Beginners who want to learn Object-Oriented Programming with Python
Developers who want to write structured, flexible, and scalable code
Engineers preparing for coding interviews and system design discussions
Anyone looking to improve their understanding of software design principles
Programmers transitioning to Python from other languages
This course is structured with clear explanations, hands-on coding exercises, and industry-relevant examples. By the end, you will be able to design and develop Python applications that follow best practices and professional coding standards.