Certified Tester AI Testing (CT-AI) Version 2.0
Overview
The ISTQB® Certified Tester AI Testing (CT-AI) v2.0 certification focuses on testing AI-based systems, including machine learning systems and generative AI systems such as large language models. It provides the knowledge required to design and execute tests for AI-based systems, addressing their specific characteristics, including probabilistic behavior, non-determinism, and reliance on data. It also introduces AI-specific quality characteristics relevant to testing AI-based systems.
The syllabus follows a lifecycle-based approach, including input data testing, model testing, and ML development testing, together with relevant test approaches for modern AI-based systems.
Note: The CT-AI v2.0 certification replaces CT-AI v1.0. Candidates interested in using generative AI to support testing activities should consider the ISTQB® Certified Tester Testing with Generative AI (CT-GenAI) certification, which focuses on the application of generative AI in the testing process.
Audience
The ISTQB® Certified Tester AI Testing (CT-AI) v2.0 certification is aimed at individuals involved in testing AI-based systems, including:
- Testers, test analysts, and test engineers
- Test managers
- Test consultants
- Data analysts and data scientists
- Software developers involved in developing AI-based systems
- User acceptance testers
It is also suitable for individuals seeking a general understanding of testing AI-based systems, such as:
- Project managers
- Quality managers
- Software development managers
- Business analysts
- IT directors and management consultants
The ISTQB ® Certified Tester Foundation Level (CTFL) is a prerequisite for the CT-AI v2.0 certification.
More Information
- The other AI relates syllabi from A4Q, AiU and CSTQB/KSTQB will be valid to October 12th 2022
- Accredited courses require accreditation of training materials, as described in the ISTQB® Accreditation Process
- Holders of the A4Q, AiU and KSTQB & CSTQB AIT previous versions continue to hold a valid certification
Training is available from Accredited Training Providers (classroom, virtual, and e-learning). We highly recommend attending accredited training as it ensures that an ISTQB® Member Board has assessed the materials for relevance and consistency against the syllabus.
Self-study, using the syllabus and recommended reading material, is also an option when preparing for the exam
Exam Structure
- No. of Questions: 40
- Total Points: 44
- Passing Score: 29
- Exam Length (mins): 60 (+25% Non-Native Language)
Business Outcomes
Individuals who hold the ISTQB® Certified Tester- AI Testing certification should be able to accomplish the following business outcomes:
- Understand the current state of AI, including generative AI.
- Experience the implementation and testing of machine learning models.
- Understand the working and testing of simple neural networks.
- Understand the specific AI quality characteristics defined by ISO/IEC 25059.
- Calculate and interpret ML functional performance metrics for machine learning models.
- Recognize the scope and importance of the two test levels that are specific to the testing of machine learning systems.
- Contribute to the development of an effective test strategy for a machine learning system.
- Design and execute test cases for machine learning systems.
Holders of this certification may choose to proceed to other Core, Agile, or Specialist stream certifications.
- Understand AI trends and evolution
- Test and improve ML model quality
- Handle AI testing challenges effectively
- Contribute to AI system strategy
- Design and run AI tests
- Define infrastructure for AI testing
Download Materials
General Files