ISTQB CT-AI

Description

The Certified Tester AI Testing 2.0 (CT-AI) qualification is aimed at professionals seeking to deepen their understanding of artificial intelligence, including machine learning and generative AI, with a focus on testing AI-based systems and using AI to support testing.

Holders of the ISTQB® Certified Tester – AI Testing certification are able to:

• Understand key AI concepts, technologies, and current industry trends
• Distinguish between types of AI, including machine learning and generative AI
• Understand the lifecycle of ML systems, from data preparation to deployment
• Identify and address testing challenges such as non-determinism, bias, drift, limited explainability, and safety risks
• Apply risk-based testing strategies tailored to AI and ML systems
• Design and execute test cases using statistical approaches and alternative test oracles
• Apply data-focused testing techniques, including data quality, representativeness, bias detection, and dataset constraint testing
• Use and interpret ML performance metrics to evaluate model behavior
• Apply AI-specific testing techniques such as adversarial, metamorphic, back-to-back, and A/B testing
• Understand deployment testing approaches (e.g., canary and shadow testing) and monitor models in operation (e.g., drift detection)
• Leverage AI to support and enhance software testing activities

Chapter 1: Introduction to Artificial Intelligence (AI)

Chapter 2: Quality Characteristics for AI-Based Systems

Chapter 3: Machine Learning (ML)

Chapter 4: Testing AI-Based Systems

Chapter 5: Input Data Testing for Machine Learning Systems

Chapter 6: Model Testing for Machine Learning Systems

Chapter 7: Machine Learning Development Testing