What you'll learn

QA teams increasingly face the challenge of maintaining large, brittle test suites while being asked to ship faster. In this course, AI for Intelligent Testing and QA, you'll gain the ability to apply machine learning across the full testing lifecycle — from self-healing automation to predictive defect analysis. First, you'll explore how ML can detect and adapt to UI changes automatically, identify flaky tests, and perform visual regression testing. Next, you'll discover how AI analyzes code history and requirements to generate and prioritize test cases, reducing manual effort and surfacing critical risks first. Finally, you'll learn how to implement defect prediction models, correlate bugs with code complexity, and use AI to accelerate failure triage. When you're finished, you'll have the skills and knowledge to build an intelligent, resilient QA pipeline that reduces manual maintenance and improves release confidence.