Ai‑Powered Qa Mastery: Chatgpt, Copilot & Prompt Engineering

Use ChatGPT & Github Copilot to write smarter tests, automate faster, and grow your QA career.

What you'll learn

The difference between AI, ML, Generative AI, and LLMs—and why it matters for QA

How to prompt ChatGPT effectively for test planning, design, and reporting

How to use GitHub Copilot to write and refactor automated UI/API tests

How to “vibe code” test automation—even if you're new to JavaScript

Ethical guidelines: what not to share with AI tools, and how to stay secure

How to build multi-step QA workflows with prompts

Requirements

No coding knowledge

No prior AI experience

Computer with a Chrome browser

ChatGPT account

Github account

Visual Studio Code

Description

Whether you're a manual tester looking to get into automation or a QA engineer curious about how AI can help, but not replace you, this course is for you.In this hands-on course, you'll learn how to use tools like ChatGPT and GitHub Copilot to boost your productivity, reduce repetitive work, and accelerate your testing workflow. No deep coding experience required! We’ll guide you through everything step by step.We'll start with the basics: what AI is (and isn’t), how it fits into QA, and how to prompt tools like ChatGPT to generate test cases, write automation scripts, and even help with bug reporting. From there, you’ll build confidence using GitHub Copilot to generate and refactor real automated tests in Playwright, while learning how to review and improve what the AI gives you.This isn’t just “watch a tool do stuff.” You’ll actually learn how to guide AI tools like a QA pro, because you still drive the logic. AI just helps you get there faster.Tools We’ll Use:ChatGPT (Plus version recommended)GitHub Copilot in Visual Studio Code (Pro version recommended)Playwright (for test automation examples)JavaScript (beginner-friendly)By the end of this course, you’ll understand how to confidently use modern AI tools to make your QA work faster, smarter, and a lot more fun.

Overview

Section 1: Getting Started

Lecture 1 Welcome to the Course

Lecture 2 Real-World AI Workflows for QA

Lecture 3 Who This Course Is For

Lecture 4 Getting the most out of this course

Lecture 5 Setting Expectations: You’re Still the QA Pro

Lecture 6 Setting Up ChatGPT Account

Lecture 7 Setting Up GitHub Account

Lecture 8 Installing Visual Studio Code

Lecture 9 How assignments work in this course

Lecture 10 Additional Resources

Section 2: Crash Course – What Is AI? What are LLMs?

Lecture 11 AI vs Machine Learning vs Generative AI vs LLMs

Lecture 12 LLM Architecture & Training Basics

Lecture 13 Tokens, Prompts, and How AI Understands You

Lecture 14 Tokens in Practice

Lecture 15 Tokenizer Challenge

Lecture 16 Understanding Hallucinations and How to Avoid Them

Section 3: Prompting Like a Pro

Lecture 17 Prompting 101

Lecture 18 Iterative Prompting

Lecture 19 Safe Prompting: What Not to Share with AI

Lecture 20 Prompt Engineering Frameworks

Lecture 21 Prompting Techniques

Lecture 22 ChatGPT Web Layout Overview

Lecture 23 Using Custom Instructions in ChatGPT

Lecture 24 Assignment: Create Your Own Personalization Settings in ChatGPT

Lecture 25 Important note about prompting results

Section 4: Test Design with AI

Lecture 26 Using AI for Test Case Design

Lecture 27 Generating Test Scenarios from Requirements

Lecture 28 Equivalence Partitioning & Boundary Testing with ChatGPT

Lecture 29 Negative Testing & Edge Cases Using Prompts

Lecture 30 AI‑Assisted Requirement Analysis & Test Planning

Lecture 31 Generative Test Data & Fuzzing

Lecture 32 AI for Test Environment Setup

Lecture 33 Assignment: Designing Better Test Cases with AI

Section 5: Exploratory Testing and Bug Reporting with AI

Lecture 34 AI-Augmented Exploratory Testing

Lecture 35 Real World Exploratory Testing Examples

Lecture 36 Using AI to Suggest Exploratory Scenarios

Lecture 37 Capturing Insights and Observations with AI Help

Lecture 38 Smarter Bug Reporting with AI

Lecture 39 AI-Assisted Bug Reporting

Lecture 40 Assignment: Exploratory Testing with AI as Your Partner

Section 6: Intro to GitHub Copilot for QA Engineers

Lecture 41 What Is GitHub Copilot and How Does It Work?

Lecture 42 VS Code Overview

Lecture 43 CLI Commands Basics

Lecture 44 Installing and Configuring Copilot in VS Code

Lecture 45 Installing Node.js

Lecture 46 Installing GIT

Lecture 47 Getting to know VS Code with Github Copilot

Lecture 48 Enhancing Github Copilot

Lecture 49 Copilot Prompt Examples for Testers

Lecture 50 Assignment: Turn Plain English into JavaScript with Copilot

Section 7: Vibe Coding

Lecture 51 Vibe Coding: What We’ll Build

Lecture 52 Vibe Coding: Test Data Generator CLI App

Lecture 53 Assignment: Lorem Ipsum CLI

Lecture 54 Vibe Coding: Mini Test Tools Service

Lecture 55 Assignment: Lorem Ipsum Service

Lecture 56 Vibe Coding: QA Boundary Web App

Lecture 57 Assignment: Lorem Ipsum Web App

Section 8: Test Automation with GitHub Copilot

Lecture 58 Using AI to Write Automated Tests

Lecture 59 DevTools & Selectors 101

Lecture 60 Writing UI Tests with Copilot: Setup and Running First Test

Lecture 61 Writing UI Tests with Copilot: Adding Run and Report Scripts

Lecture 62 Writing UI Tests with Copilot: Creating Page Objects

Lecture 63 Writing UI Tests with Copilot: Refactoring the Tests

Lecture 64 Writing API Tests with Copilot

Lecture 65 Assignment: Using Copilot to Generate Playwright Tests

Section 9: Using Copilot & ChatGPT as QA Agents

Lecture 66 What Is an AI Agent?

Lecture 67 Using ChatGPT as an AI Agent: Log Analysis

Lecture 68 Using ChatGPT as an AI Agent: Website Testing

Lecture 69 Using GitHub Copilot as an AI Agent: Test Run Analysis

Lecture 70 Assignment: Using an AI Agent in ChatGPT

Section 10: Ethics and Practical Limitations of AI in QA

Lecture 71 Ethics and Practical Limitations of AI in QA

Lecture 72 Security Risks, Compliance, and Corporate IT Policies

Lecture 73 Approved vs. Unapproved Tools

Lecture 74 PII, PHI, and Proprietary Code: What Not to Share

Section 11: Final Project

Lecture 75 Final Project: Building a Prompt Library

Section 12: Course Wrap-Up and Next Steps

Lecture 76 What AI Can’t Do

Lecture 77 Where to Go Next

Lecture 78 Closing Thoughts + Thank You

Section 13: BONUS SECTION

Lecture 79 Bonus Lecture

Manual testers ready to explore automation with support from AI,QA engineers looking to add AI tools to their workflow,SDETs who want to prototype faster or experiment with Copilot,Curious tech professionals wondering “Can AI actually help me test better?”