2026 - ISTQB AI Testing (CT-AI) Certification - Crash Course

<div>A <b>complete practical course to make you understand AI Testing with ISTQB exam readiness</b>.</div><div>Traditional software testing assumes predictable logic and fixed expected outputs. AI systems don’t work that way. They learn from data, evolve over time, behave probabilistically, and often operate as black boxes. This shift breaks many traditional testing assumptions. In this course, you will learn how to test AI-based systems the right way, using globally accepted ISTQB AI Testing (CT-AI) principles, explained clearly and practically for testers.</div><div><br></div><div>This course starts by building strong foundations. You will first understand what AI really is, how AI-based systems differ from conventional software, and why new testing strategies are required. You’ll then learn machine learning fundamentals — supervised, unsupervised, and reinforcement learning — not as a data scientist, but from a tester’s mindset.</div><div><br></div><div>As the course progresses, you’ll explore the complete ML lifecycle, focusing on what testers must validate at each stage: data preparation, training, validation, testing, deployment, and ongoing monitoring. You’ll learn how poor data quality, bias, imbalance, and mislabeling directly impact model behavior and test outcomes.</div><div><br></div><div>You will deeply understand ML performance metrics, their limitations, and how to detect overfitting and underfitting. The course then moves into testing AI-specific quality characteristics such as fairness, ethics, safety, transparency, interpretability, and explainability (XAI).</div><div><br></div><div>Finally, you’ll apply AI-specific testing techniques like adversarial testing, metamorphic testing, data poisoning, A/B testing, and exploratory testing, and also learn how AI itself can be used to enhance testing through test generation and defect prediction.</div><div><br></div><div>This course strictly follows the ISTQB CT-AI syllabus and prepares you with both conceptual clarity and exam confidence, making it ideal for testers, QA engineers, and test managers moving into AI-driven systems.</div><div><br></div><div>Course FAQs</div><div><ul><li><span style="font-size: 1rem;">ISTQB Syllabus-Oriented</span></li><li><span style="font-size: 1rem;">Course content prepared entirely based on the official ISTQB syllabus.</span></li></ul></div><div><span style="font-size: 1rem;">Practical Approach</span></div><div><ul><li><span style="font-size: 1rem;">Concepts explained with real-world examples so you can easily relate them to your work.</span></li><li><span style="font-size: 1rem;">Comprehensive Learning Structure</span></li><li><span style="font-size: 1rem;">Each concept is followed by supplementary reading materials.</span></li><li><span style="font-size: 1rem;">Chapter-by-chapter exam simulation quizzes to build confidence.</span></li><li><span style="font-size: 1rem;">Full-length quiz tests at the end to ensure complete preparation.</span></li><li><span style="font-size: 1rem;">Designed to familiarize you with the actual exam pattern.</span></li></ul></div><div><span style="font-size: 1rem;">Success Strategy</span></div><div><ul><li><span style="font-size: 1rem;">A thorough understanding of the course content, combined with consistent practice of all quizzes, will set you up to successfully clear the ISTQB exam.</span></li></ul></div><div><br></div><div>Finally, I strongly encourage you to dedicate quality time to the quizzes—not just to find the right answer, but to carefully analyze why all the other options are incorrect. This will sharpen your reasoning process, improve conceptual clarity, and build the confidence needed to succeed in the real exam</div>

What you'll learn:

• Learn Foundations of AI & Machine Learning for Testers
• 200+ practice quizzes designed to simulate the actual exam format.
• End-to-End Machine Learning Lifecycle & Data Testing
• ML Model Evaluation & Performance Testing
• Testing AI-Based Systems & AI-Specific Quality Characteristics
• Advanced AI Testing Techniques & Test Oracles
• Using AI for Testing & ISTQB CT-AI Exam Readiness
• Understand Bias, Ethics, Fairness & Explainable AI (XAI) in Real Systems
• Handle Non-Deterministic Behavior, Concept Drift & Production AI Risks