Gen AI Test Automation- Selenium Playwright Copilot Claude

Step into the future of QA with AI-powered test automation.

In this course, you’ll learn how to combine industry-standard tools like Selenium and Playwright with modern AI assistants such as GitHub Copilot, Claude Code, and Amazon Q to build faster, smarter, and more scalable automation workflows.

Whether you’re starting your automation journey or looking to level up your existing skills, this course is designed to help you work more efficiently, write better tests, and adopt the latest AI-driven development practices.

It practically demonstrates how to build your own AI Agents. You can also migrate your existing test cases from Selenium to Playwright.

By the end of this course, you will be able to:

• Build end-to-end test automation frameworks using Selenium and Playwright

• Use AI tools like GitHub Copilot, Claude Code, and Amazon Q to accelerate development

• Create data-driven, API, and performance tests using modern techniques

• Design and implement AI-assisted workflows and automation agents

• Migrate existing Selenium tests to Playwright for improved reliability and speed

• Apply MCP-based workflows for advanced automation use cases

• Claude Skills — reusable Markdown-based capabilities that Claude loads automatically, so you stop repeating yourself and start getting consistent results every time. From your first SKILL to multi-file production Skills with validator scripts and evaluation frameworks, this course covers everything across four hands-on modules.

This course focuses on practical, real-world implementation.

You’ll not only learn how automation works, but also how to:

• Integrate AI into your daily QA workflow

• Improve productivity with intelligent coding assistance

• Build solutions aligned with modern engineering practices

• Work with tools and techniques used in real projects

What you’ll build

Throughout the course, you’ll create:

• UI automation scripts using Selenium and Playwright

• AI-assisted test cases using GitHub Copilot

• API testing workflows with backend validation

• Performance testing integrations

• Database validation scenarios

• AI-powered automation workflows and agents

• MCP-based integrations for advanced scenarios

Tools & Technologies covered

• Selenium WebDriver

• Playwright

• GitHub Copilot

• Claude Code

• Amazon Q

• MCP (Model Context Protocol)

• API Testing (Axios)

• Performance Testing (Artillery)

• Database Testing Tools

• Agent Skill

This comprehensive program integrates cutting-edge Generative AI, and Vibe Coding throughout every lesson. You'll master revolutionary AI-assisted development techniques used by top tech companies.

Course Curriculum

Section 1: Introduction & GitHub Copilot Fundamentals

• Course agenda and learning roadmap

• Introduction to modern AI-powered testing

• Exploring key features of GitHub Copilot for QA professionals

• Setting up your AI-assisted testing environment

Section 2: Environment Setup & IDE Configuration

• Signing up for GitHub Copilot (AI pair programming setup)

• Setup inside Visual Studio Code with Copilot integration

• Optional IntelliJ setup for advanced users

• Configuring your AI-powered development workspace

Section 3: Application Setup & Form Handling

• Build a new application for "The Internet Herokuapp" testing

• Login form validations with AI assistance

• Form automation using GitHub Copilot suggestions

• Real-world web application testing scenarios

Section 4: Basic Selenium Interactions (AI-Enhanced)

• Dropdown handling with intelligent element selection

• Checkbox automation using AI-generated test patterns

• Mouse hover actions and advanced user interactions

• Alerts and popups management with Copilot assistance

• Frames and windows handling techniques

• Data tables automation and validation

Section 5: Data-Driven Testing with GenAI

• Data-driven testing fundamentals with AI optimization

• JSON data handling for API and web testing

• CSV data integration for comprehensive test scenarios

• AI-powered test data generation and management

Section 6: Validation & Debugging

• Screenshot automation and visual validation

• Console logs analysis with AI-assisted debugging

• Smart error detection and resolution techniques

• AI-powered test maintenance and optimization

Section 7: Advanced Selenium Interactions

• Drag and drop automation with precise control

• Scroll bar interactions and page navigation

• Dynamic loading and Ajax element handling

• Complex user interaction scenarios

Section 8: File Operations

• File upload automation with various file types

• File download validation and verification

• Document handling in automated testing workflows

Section 9: Performance Testing Integration

• Performance testing using Artillery framework

• Load testing integration with Selenium automation

• Performance validation and reporting

Section 10: API Testing Mastery

• API testing using Axios Client for comprehensive backend validation

• RESTful API automation and testing strategies

• Integration between UI and API testing

Section 11: GitHub Copilot - Spring Boot Java Application (Optional)

• Quick start scaffolding a Java application using Copilot

• Sorting, filtering, and pagination with AI assistance

• Excel export functionality using Copilot suggestions

• Unit testing with AI-generated test cases

• Swagger API documentation with GitHub Copilot

• Code simplification techniques using AI assistance

Section 12: Database Testing with GitHub Copilot (Optional)

• SQLTools setup in Visual Studio for database management

• Oracle Client/Driver installation and configuration

• Database connection establishment with AI guidance

• Creating products table with intelligent schema design

• Syntax error resolution using AI-powered debugging

• Test data generation with Mockaroo integration

• CSV data loading via SQL*Loader automation

• Function creation and terminal error resolution

Section 13: Amazon Q Integration

• Amazon Q installation on Visual Studio (Free Tier)

• Building chat applications using Amazon Q AI features

• AWS Services integration for enhanced testing capabilities

• Troubleshooting with AWS Resources using Amazon Q assistance

Section 14: Evolution of MCP

• Need for MCP - Current Solutions and their Limitations

• Client Server Architecture

Section 15: All About MCP

• MCP Architecture

• MCP Server Components

• MCP Transport Types

• MCP Flow - Server, Client and Host communication over Transport layer

Section 16: Hands On MCP - STDIO Transport with Cursor IDE

• Install Dependencies with UV package

• Walkthrough Weather API

• Invoke Weather API

• Getting MCP Server Ready

• MCP Host, Client and Server

• MCP Inspector

Section 17: Claude with Github using MCP and Github Access Tokens

• Integrate Claud Desktop with Github

Section 18: MCP with Github Docker

• GitHub Copilot Context optimization for better code suggestions

• Github MCP Server on local Docker and Claude Desktop

• MCP with Github, Docker and Claude

Section 19: Advanced AI Techniques

• GitHub Copilot Context optimization for better code suggestions

• Prompt Engineering for QA-specific AI interactions

• Best practices for AI-assisted test automation

Perfect For

• Manual QA Testers - Transition to AI-powered automation

• Selenium Beginners - Start with modern AI-assisted approach

• Intermediate QA Engineers - Enhance productivity with GenAI tools

• Software Developers - Add AI-powered testing to your skillset

• QA Team Leads - Implement cutting-edge automation strategies

• Career Changers - Enter the high-demand AI-powered QA field