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ISTQB® Certified Tester AI Testing (CT-AI)
The ISTQB® AI Testing (CT-AI) certification extends understanding of artificial intelligence and/or deep (machine) learning , most specifically testing AI-based systems and using AI in testing.
Description
The ISTQB® AI Testing (CT-AI) certification extends understanding of artificial intelligence and/or deep (machine) learning, most specifically testing AI-based systems and using AI in testing.
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What You Will Learn
CT-AI focuses on testing AI-based systems and on applying AI techniques in testing.
It typically requires a valid ISTQB Certified Tester Foundation Level (CTFL) certificate.
The syllabus addresses topics such as:
Chapter 1- Introduction to AI
Chapter 2- Quality Characteristics for AI-Based Systems
Chapter 3- Machine Learning (ML) – Overview
Chapter 4- ML – Data
Chapter 5- ML Functional Performance Metrics
Chapter 6- ML – Neural Networks and Testing
Chapter 7- Testing AI-Based Systems Overview
Chapter 8- Testing AI-Specific Quality Characteristics
Chapter 9- Methods and Techniques for the Testing of AI-Based Systems
Chapter 10- Test Environments for AI-Based Systems
Chapter 11- Using AI for Testing
Certification & Exam
After you complete an accredited CT-AI training based on the ISTQB syllabus v1.0, you become eligible to take the official exam for the ISTQB Certified Tester – AI Testing (CT-AI) certificate.
To become eligible for the CT-AI certification you must:
Already hold the ISTQB Certified Tester – Foundation Level (CTFL) certificate.
Attend a training course or self-study using the CT-AI syllabus v1.0.
Pass the CT-AI exam, which covers topics such as AI systems, test automation for AI, ethics, and data quality, following the exam format defined by ISTQB.
After you meet those prerequisites and pass the exam you receive the CT-AI certificate, confirming your specialised competence in testing AI-based systems.
What You Will Achieve
Individuals who hold the ISTQB® Certified Tester- AI Testing certification should be able to accomplish the following business outcomes:
Understand the current state and expected trends of AI
Experience the implementation and testing of a ML model and recognize where testers can best influence its quality
Understand the challenges associated with testing AI-Based systems, such as their self-learning capabilities, bias, ethics, complexity, non-determinism, transparency and explainability
Contribute to the test strategy for an AI-Based system
Design and execute test cases for AI-based systems
Recognize the special requirements for the test infrastructure to support the testing of AI-based systems
Understand how AI can be used to support software testing
Training Providers
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General FAQs
CT-AI is a Specialist certification about testing AI-based systems and also using AI in testing. It builds your understanding of AI and machine learning in a testing context.
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