Master the future of quality assurance with AI-powered testing.You'll learn how to harness large language models (LLMs), such as ChatGPT and GitHub Copilot, to generate, analyze, and maintain test cases with greater speed and precision.Through a progressive series of labs, you'll explore real-world techniques for AI-assisted test creation, legacy code analysis, code coverage improvement, exploratory testing, synthetic data generation, and much more. You'll also tackle the unique challenges of testing AI systems themselves, manage flaky tests, and integrate AI-generated tests into CI/CD pipelines. Ethical considerations and model limitations are addressed throughout to ensure responsible AI adoption. Updated June 2026 Module 1: Foundations of AI in TestingIntroduction to AI in Software TestingBenefits and use cases of AI for QAOverview of AI tools: GitHub Copilot, ChatGPT, Applitools, Launchable, and moreUnderstanding zero-shot and few-shot promptingModule 2: AI-Driven Test Case GenerationWriting effective prompts for test creationGenerating unit and edge case tests using LLMsPrompt patterns and strategies for maximizing test
