ISTQB AI Testing v2.0 Sample exams 2026

This course is preparation for CT-AI v2.0 exam, it will help you go through all the sections of syllabus with sample questions
You can verify your knowledge for every type of content provided to pass exam.
There is no random order of questions. It's going directly with syllabus section. It's the most convinient way of study. Study chapter/section -> Try your knowledge with questions based for specific chapter. Lot easier than study everything and randomly seeing questions.

Course is sorted like syllabus sections:

1. Introduction to AI

   • AI-based and conventional systems

   • Narrow AI, General AI, and Super AI

   • AI technologies and Generative AI

   • Hardware for machine learning systems

   • Development and hosting of AI models

   • Machine learning development frameworks

   • Regulations and standards for AI

2. Quality Characteristics for AI-Based Systems

   • AI-specific quality characteristics

   • Safety and AI

   • Acceptance criteria for AI-based systems

3. Machine Learning

   • Forms of machine learning

   • The machine learning workflow

   • Pre-trained models, fine-tuning, and RAG

   • Data preparation and dataset splitting

   • ML model evaluation and performance metrics

   • Neural networks and perceptrons

   • Neural-network coverage measures

4. Testing AI-Based Systems

   • Locked and adaptive AI-based systems

   • Statistical testing approaches

   • Test oracles for AI-based systems

   • Testing Generative AI and large language models

   • Red teaming

   • Test levels and risk-based testing for ML systems

5. Input Data Testing for Machine Learning Systems

   • Input-data risks and mitigations

   • Testing for bias

   • Data-pipeline testing

   • Data representativeness

   • Dataset constraint testing

   • Label correctness testing

6. Model Testing for Machine Learning Systems

   • ML model risks and mitigations

   • Model documentation and review

   • Functional performance testing

   • Adversarial and metamorphic testing

   • Drift testing

   • Overfitting and underfitting

   • and other