This course shows how to design and build real AI-powered automation systems, where plain-text test plans are transformed into executable automation suites, tests are run automatically, and failures are analyzed intelligently using test code, execution output, and service logs. Rather than focusing on prompt-only workflows or demos, this course takes a system-level engineering approach. You will learn how to integrate AI into existing automation frameworks in a controlled, deterministic, and reliable way, without compromising test quality or trust in results.
You will build an AI-assisted automation pipeline using Java and Spring MVC, integrate AI APIs, and design automation that is intentionally structured to work well with AI. The course also tackles one of the biggest real-world challenges in automation: a failing test does not always mean a service bug. You will learn how to use AI to analyze test code, test execution output, and service logs together to reduce investigation time and produce clear, human-readable explanations of what actually went wrong.
