ISTQB CT-AI
ISTQB® CT - AI Testing (Version 2.0)
Descripción
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
Público objetivo
The Certified Tester AI Testing (CT-AI) Version 2.0 qualification is designed for professionals who want to build practical, real-world skills in testing AI-based systems and using AI to enhance testing. It is ideal for software testers, QA engineers, developers, and data professionals working with machine learning or generative AI, as well as anyone involved in delivering high-quality, AI-driven solutions. Whether you are already working with AI or preparing for future projects, this certification helps you understand the risks, challenges, and best practices needed to ensure reliable, trustworthy AI systems.
Requisitos
- Have successfully passed the ISTQB® CTFL Certification exam and hold the certificate.
- First experience in AI projects is recommended, but not required.
El precio del examen global varía según la certificación y su ubicación geográfica.
Reserve un Examen de Certificación
Exámenes Online (Brightest Private Exams)
Exámenes electrónicos para individuos, administrados por un experto de Pearson Vue en tiempo real, a través de una cámara web (también disponible ahora para los exámenes ISTQB).
Exámenes en Centros Acreditados (Brightest Center Exams)
Disponible en varios idiomas, en más de 5200 centros de exámenes, con un registro simplificado a través de la página Brightest del sitio web de Pearson Vue.
Exámenes en Grupo (Brightest Green Exams)
Exámenes electrónicos para grupos con un mínimo de 6 participantes, disponibles en seis idiomas diferentes, en cualquier parte del mundo.
Exámenes en papel (Brightest Paper Exams)
El formato clásico de examen, dirigido a grupos de al menos 6 participantes, en un número creciente de idiomas.