ISTQB Certified Tester – AI Testing (CT-AI)
iLAB’s ISTQB Certified Tester – AI Testing (CT-AI) Course
Course Overview
The ISTQB Certified Tester – AI Testing (CT-AI) course provides foundational knowledge on how to test AI-based systems and how to use AI to improve software testing processes. Designed for software testers, developers, and QA professionals, this course explores the complexities of testing machine learning models, addresses AI-specific quality characteristics like bias and adaptability, and introduces AI-powered testing tools. It is an essential step for professionals looking to specialize in this rapidly evolving area of software quality.
Key Learning Areas
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Introduction to AI and AI-Based Systems: Understand core AI concepts, technologies, and frameworks. Explore how AI impacts software testing and how to leverage AI as a Service (AIaaS).
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Quality Characteristics of AI-Based Systems: Evaluate unique attributes such as flexibility, autonomy, bias, and ethical considerations, along with regulatory and safety issues.
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Machine Learning Fundamentals: Learn about supervised, unsupervised, and reinforcement learning models, model evaluation metrics, and concepts like overfitting and underfitting.
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Testing AI-Based Systems: Develop effective testing strategies for AI, including input validation, model testing, acceptance testing, and detection of automation bias or concept drift.
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AI Testing Methods and Techniques: Apply methods like adversarial testing, metamorphic testing, A/B testing, and experience-based testing to uncover critical issues.
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Using AI in Software Testing: Explore AI-driven approaches for generating test cases, predicting defects, optimizing regression suites, and automating UI testing and defect analysis.
Internationally Accredited Software Quality Assurance Training
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