AI Meets QA: A Full-Day Journey Through Testing, Tools, and Techniques
Speaker
Target audience
Basic (no prior knowledge)
Description
How do you test AI-based systems? What challenges do self-learning systems introduce? Artificial Intelligence and, in particular, Machine Learning are increasingly embedded in everyday applications, creating new challenges for software testing. Traditional test approaches are often insufficient due to the adaptive, probabilistic, and data-driven nature of AI systems, making AI-specific testing techniques essential.
This workshop introduces key concepts in AI and machine learning from a tester’s perspective. It covers AI-specific quality characteristics, testing activities during and after the training of machine learning models, and appropriate test levels, approaches, and techniques for testing AI-based systems.
The workshop is a taste of the full ISTQB® AI Testing (CT-AI) 3-day course with exciting AI and testing knowledge and exercises. It is aligned with the latest CT-AI syllabus from May 2026. It lowers the barrier to further learning, whether through the full course or independent study toward the ISTQB CT-AI certification.
The workshop is aimed at professionals involved in testing AI-based systems. This includes testers, test analysts, data analysts, developers, test engineers, consultants, managers, and user acceptance testers. It is also suitable for anyone seeking a foundational understanding of AI testing, such as project and quality managers, business analysts, operations team members, IT leaders, and management consultants.
You will learn
How to use AI-related quality characteristics for better testing
How to use test techniques to deal with typical AI challenges
What test approaches work in testing AI