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Gen AI for QA: Test Automation with Claude & GitHub Copilot

Name: Gen AI for QA: Test Automation with Claude & GitHub Copilot
Rating: 4.7 (78 reviews)

Real & practical AI Testing for QA Engineers: Claude Code, GitHub Copilot, Playwright, MCP & Prompt Engineering

Role Play

Created byAlex Dan • 300K+ Students

Last updated 6/2026

English

What you'll learn

Apply Prompt Engineering techniques to improve QA test case generation
Use GitHub Copilot for testing with Playwright and Selenium projects
Build AI agents and MCP integrations for QA automation workflows
Generate test plans, test cases, and test data using LLM tools
Leverage Generative AI for software testing across your QA process
Integrate Playwright MCP into AI powered test automation
Run local LLM models privately with Ollama inside GitHub Copilot and Claude Code
Apply GenAI for QA across the full testing lifecycle — from planning to execution
Install and configure MCP servers to connect AI agents to real testing tools

Course content

11 sections • 63 lectures • 3h 55m total length

Welcome to Generative AI for QA3:00
Discover how AI powered quality assurance can transform your daily work, with sections on prompt engineering, AI assisted coding with GitHub Copilot, Cloud Code, Playwright, and AI powered API testing.
Udemy tips2:18
Tools for AI assisted QA2:03
Course resources0:06

Introduction to Prompt Engineering for QA2:04
Gain practical skills in prompt engineering for QA by designing, refining, and testing prompts to improve accuracy and relevance, using Claude or other chat tools.
Prompt Engineering Principles for Software Testing4:06
Prompt Constraints for Reliable AI Testing Results2:37
Context Engineering for QA Automation Prompts5:54
Prompt Patterns for QA Engineers5:25
Common Prompt Engineering Mistakes in Software Testing2:06
Using AI as a Learning Tool for QA Engineers2:19
Quick Prompt Engineering Tip for Faster Test Automation1:35
Explore a quick prompt engineering tip for faster test automation by recording a prompt to generate realistic test data, including valid and invalid cases for a registration form.
Section quizz

Introduction to GitHub Copilot for Test Automation3:33
GitHub Copilot installation and first contact3:24
Optional: GitHub Copilot installation for IntelliJ2:16
Initializing a Playwright Test Automation Project1:43
Initialize a Playwright test project with GitHub Copilot in VS Code, using TypeScript and test folder. Install browsers, remove sample code, and start writing tests for awesome pizza with Copilot.
Generating a Test Plan with GitHub Copilot5:45
AI Powered Test Cases Review with GitHub Copilot5:30
Review and fix tests with GitHub Copilot, resolving failing cases and unicode issues, and replace hard-coded menu data with dynamic checks against backend data.
Completing Test Automation with Copilot for Playwright3:01
Playwright MCP for QA Automation5:51
AI Powered Coding Assistance with GitHub Copilot for Testing3:10
Page Object Model with GitHub Copilot and Playwright2:49
Section quizz
Adopting GitHub Copilot

Introduction to Claude Code for Test Automation1:44
Claude Code installation3:01
First contact with Claude Code1:59
Playwright project init with Claude3:44
Generating a Test Plan with Claude Code4:30
Generate a testing strategy for the address app using Cloud Code in the VS Code extension, analyze the Playwright project, then write and save a comprehensive file-based test plan.
AI Powered Tests with Claude4:37
Claude.md file4:52
Completing the testing suite and fixing tests with Claude Code3:41
Complete the testing suite for the dump application by using cloud code to generate seven specification files and run tests with Playwright. Fix assertion issues and ensure all tests pass.
Claude Code tips for QA3:36
Section Quizz
Adopting Claude Code

Section Intro0:42
Explore agentic AI and MCP servers, and extend their capabilities in chat and AI applications with MCPs. Analyze Chrome DevTools MCP and Playwright MCP designed for QA work.
Introduction to Agentic AI for Software Testing5:53
Model Context Protocol (MCP) for QA Engineers4:33
Learn how the model context protocol, or MCP, standardizes AI tools for external systems. See a pizza web store MCP example to enable AI agents like Copilot to order pizza.
Finding and Evaluating MCP Servers4:39
MCP servers requirements3:58
Installing MCP Servers in Claude Code4:12
Install a basic MCP server in Claude via Cloud Desktop, add the Airbnb MCP entry to a valid JSON, restart Cloud, and verify by retrieving apartments and a map.
Installing MCPs in GitHub Copilot6:06
Chrome DevTools MCP for AI-Powered QA Automation9:18
Playwright MCP Explained: AI Agents for Test Automation5:45
AWS Documentation MCP Server for QA Engineers4:27
Section quizz
Adopting MCP servers

Section Intro: Building AI Agent Skills0:33
What Are Skills?2:02
Define AI skills as reusable instructions for AI clients—first introduced by Claude and used by Copilot and ChatGPT—loaded into context to speed up tasks and reduce repetition, stored as skill.md.
Your First Skill: Hello World Walkthrough10:57
Build your first ai skill by creating a hello world skill with a skill.md, a name and description, and a template, then extend with scripts like awesomename.js.
Sample Skills for Test Automation (Real QA Examples)4:55
Skill Creation Tips1:51
Where to Find & Share Skills5:01
Discover ready-made ai skills for test automation and learn to install them via mpx, then integrate them into your project using resources like ClaudeSkills and skills.sh.

Section intro3:55
Ollama installation1:50
Install ollama by downloading from ollama.com, choose your platform (Windows, Linux, or Mac OS), install via installer or terminal, and use ollama list to select models suited to your hardware.
Selecting and Installing a Local LLM6:41
Select and install a local llm by pulling the QUIN 3.5 model with 9 billion parameters on OLAMA and running it offline.
Ollama inside Claude Code2:00
Ollama inside GitHub Copilot1:26

Requirements

Basic programming and AI usage.

Description

Are you a QA engineer, automation tester, or manual tester ready to future-proof your career? This course is the most practical, hands-on guide to AI testing available — built specifically for the software testing profession.

Whether you're exploring AI-powered testing for the first time or looking to level up with tools like GitHub Copilot and Claude Code, this course takes you from zero to confident in GenAI for QA.

What you will learn

Use GitHub Copilot for test automation — generate test cases, review code, and build a full Playwright project with AI assistance
Use Claude Code for QA automation — create test plans, write AI-powered tests, and configure your workflow with CLAUDE md
Master Playwright MCP — the most powerful combination of Agentic AI and test automation available today
Learn Prompt Engineering for QA — principles, patterns, and mistakes that define expert prompting
Connect AI agents to real tools with MCP servers: Chrome DevTools, AWS documentation, and databases
Run local LLMs privately with Ollama inside GitHub Copilot and Claude Code

Who this is for

QA engineers and automation testers who want to work smarter with AI
Manual testers moving into AI-assisted or automated testing
Test leads evaluating GenAI tools for their teams
Anyone exploring Generative AI for software testing in a practical, tool-first way

No prior AI experience needed.

Tools covered

GitHub Copilot, Claude Code, Playwright, Playwright MCP, Chrome DevTools MCP, AWS Documentation MCP, Ollama, and core Prompt Engineering techniques.

Most AI testing courses are too theoretical or focused on a single tool. This course covers the full landscape of GenAI for QA — from prompt engineering fundamentals to Agentic AI and MCP servers — with real hands-on projects throughout.

Enrol now and start using GitHub Copilot, Claude Code, and Playwright MCP to transform how you test software.

Who this course is for:

QA engineers and testers who want to leverage the power of AI into their work

Gen AI for QA: Test Automation with Claude & GitHub Copilot

What you'll learn

Explore related topics

Course content

Course Introduction4 lectures • 7min

AI powered Quality Assurance - introduction5 lectures • 26min

Prompt Engineering for QA: Getting the Best from AI8 lectures • 26min

Halfway discussion1 lecture • 2min

Hands on: AI assisted coding - GitHub Copilot and Playwright11 lectures • 37min

Hands on: AI assisted testing - Claude Code10 lectures • 32min

AI Powered API Testing for QA Engineers3 lectures • 13min

AI Agents & MCP for QA Automation11 lectures • 50min

Agentic AI: Skills for QA engineers6 lectures • 25min

Going offline: Local Models for secure and free AI5 lectures • 16min

Requirements

Description

Who this course is for: