Software Testing with Generative AI: ISTQB CT-GenAI Preparation

Generative AI is reshaping the software testing landscape, making it essential for QA professionals to understand how to leverage large language models safely and effectively. This text-based course helps you bridge the gap between traditional testing methodologies and modern AI-driven QA practices. You will transition from manual test preparation to AI-augmented test engineering. By studying core concepts, prompt design patterns, and risk mitigation strategies, you will build the foundational knowledge required to apply generative AI to test automation, test case generation, and test maintenance, while aligning with the ISTQB Certified Tester Generative AI syllabus. What you'll learn: - Understand the core terminology, capabilities, and limitations of LLMs in software testing - Design effective prompt engineering patterns tailored for test case generation and bug reporting - Identify and mitigate risks associated with generative AI, including bias, hallucinations, and data privacy concerns - Apply AI tools to streamline test automation script creation and test data generation - Analyze strategies for testing AI-based systems and maintaining AI-generated test suites - Prepare for the ISTQB CT-GenAI certification exam with targeted conceptual reviews The course begins with foundational definitions of generative AI and its role in software quality assurance, before moving into practical prompting strategies, automation workflows, and risk management. You will progress through clear, written explanations and code-based examples designed to reinforce your learning. This course is designed for beginner to intermediate software testers, QA analysts, and developers who want to integrate AI into their workflows. No prior experience with generative AI or machine learning is required. Start reading today to elevate your testing career with the power of generative AI.