Updated June 2026

Object-Oriented Programming with Python and AI Tools

Class Duration

28 hours of live online training delivered over 4-5 days

Student Prerequisites

Experience with Python programming
Some experience with object-oriented programming in Python or another language is recommended

Target Audience

Python developers, backend engineers, data and QA automation coders, DevOps toolsmiths, architects, and team leads seeking sharper OOP: master classes and typed interfaces, apply SOLID and patterns, refactor with tests and DI, pass ruff/mypy, debug in VS Code, and use AI to ship cleaner APIs and scalable features. Teams wanting a deeper, AI-free treatment of the same principles can also look at Design Patterns and SOLID with Python.

Description

The Object-Oriented Programming with Python training course is for students with Python experience desiring to learn more about object-oriented programming (OOP) using the Python language. The class starts with coverage of Python classes and their many features, then proceeds into the core principles and practices of OOP. From there, SOLID and object-oriented design patterns are explained, discussed, and applied. Throughout the class, AI tools are used to learn OOP and to apply it to real software programming. Finally, students transition from being programmers to software engineers, using AI tools to do the programming for them while they plan the coding changes with OOP patterns.

Learning Outcomes

Model a domain with Python classes; validate with unit tests.
Refactor using encapsulation, inheritance, composition, and polymorphism.
Define typed interfaces with dataclasses and ABCs/Protocols; pass ruff and mypy.
Debug object collaborations in VS Code to find and fix defects.
Spot SOLID violations and add abstractions without breaking tests.
Implement appropriate design patterns and justify the choice.
Convert legacy code to OO with dependency injection to reduce coupling, writing unit tests and test doubles that pin behavior during refactors.
Use AI tools to draft code, tests, and refactor plans, critique outputs, and deliver a small feature using two patterns and SOLID with a brief design and test report.

Training Materials

Comprehensive courseware is distributed online at the start of class. Courseware is distributed via GitHub in the form of documentation and extensive code samples. Students practice the topics covered through challenging hands-on lab exercises. All students receive a downloadable MP4 recording of the training.

Software Requirements

Students will need a free, personal GitHub account to access the courseware. Students will need permission to install Python and Visual Studio Code on their computers. Also, students will need permission to install Python Packages and Visual Studio Code extensions. If students are unable to configure a local environment, a cloud-based environment can be provided.

Training Topics

Object-Oriented Programming Foundations

What is Object-Oriented Programming?
What are Patterns?
What is SOLID?
How is Python an Object-Oriented Programming Language?

Development Environment

Configure VS Code for Python development
Code Reformatting with Ruff
Linting with Ruff and MyPy
Debugging Python Scripts with VS Code

Python Classes

Defining a Class
Instance and Class Members
Inheritance
Multiple Inheritance
Getter/Setter Properties

Principles and Practical Object-Oriented Programming

Encapsulation
Polymorphism
Inheritance
Composition
Shared Variable Context for Functions

SOLID Programming

Single Responsibility Principle
Open-Closed Principle
Liskov Substitution Principle
Interface Segregation Principle
Dependency Inversion Principle

Component Design

Component Cohesion
Component Coupling

Creational Design Patterns

Abstract Factory
Factory
Builder
Prototype
Singleton

Behavioral Design Patterns

Chain of Responsibility
Command
Interpreter
Iterator
Mediator
Observer
Strategy
Memento
State
Template Method
Visitor

Structural Design Patterns

Adapter
Bridge
Composite
Decorator
Façade
Flyweight
Proxy

AI Tools and OOP Programming

AI Tools and Programming Patterns
Refactor Legacy Code to use Patterns
Transform from One Pattern to Another
Discover Patterns in Code
Discuss Pattern Options
Plan Software Changes with AI Tools and Patterns