ISQI ISTQB Certified Tester AI Testing (v1.0) : CT-AI_v1.0_World

  • Exam Code: CT-AI_v1.0_World
  • Exam Name: ISTQB Certified Tester AI Testing (v1.0)
  • Updated: Oct 06, 2026     Q & A: 40 Questions and Answers

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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

SectionObjectives
ML Functional Performance Metrics- Performance Evaluation
  • 1. F1 Score
  • 2. Accuracy
  • 3. Recall
  • 4. Precision
Testing AI-Specific Quality Characteristics- Quality Validation
  • 1. Robustness Testing
  • 2. Explainability Assessment
  • 3. Fairness Testing
Machine Learning- ML Fundamentals
  • 1. Machine Learning Overview
  • 2. Supervised and Unsupervised Learning
  • 3. Training and Validation
Using AI for Testing- AI-Assisted Testing
  • 1. Defect Prediction
  • 2. Test Data Generation
  • 3. Test Automation Support
ML Data- Data Quality
  • 1. Data Bias
  • 2. Data Collection
  • 3. Data Preparation
Testing AI-Based Systems Overview- AI Testing Fundamentals
  • 1. Test Strategy
  • 2. AI Test Lifecycle
  • 3. Risk-Based Testing
ML Neural Networks and Testing- Neural Networks
  • 1. Neural Network Basics
  • 2. Testing Neural Networks
Quality Characteristics for AI-Based Systems- AI-Specific Quality Attributes
  • 1. Flexibility and Adaptability
  • 2. Ethics
  • 3. Evolution
  • 4. Bias
  • 5. Transparency and Explainability
  • 6. Autonomy
Test Environments for AI-Based Systems- AI Test Infrastructure
  • 1. Data Management
  • 2. Monitoring and Maintenance
  • 3. Environment Configuration
Introduction to AI- AI Fundamentals
  • 1. AI Definitions and Concepts
  • 2. AI Technologies
  • 3. AI as a Service
  • 4. AI-Based vs Conventional Systems
  • 5. AI Development Frameworks
Methods and Techniques for Testing AI-Based Systems- Test Design Techniques
  • 1. Model Testing
  • 2. Scenario-Based Testing
  • 3. Data-Oriented Testing

ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:

Question #1

"AllerEgo" is a product that uses sell-learning to predict the behavior of a pilot under combat situation for a variety of terrains and enemy aircraft formations. Post training the model was exposed to the real- world data and the model was found to bebehaving poorly. A lot of data quality tests had been performed on the data to bring it into a shape fit for training and testing.
Which ONE of the following options is least likely to describes the possible reason for the fall in the performance, especially when considering the self-learning nature of the Al system?
SELECT ONE OPTION

  • A. The unknown nature and insufficient specification of the operating environment might have caused the poor performance.
  • B. The fast pace of change did not allow sufficient time for testing.
  • C. There was an algorithmic bias in the Al system.
  • D. The difficulty of defining criteria for improvement before the model can be accepted.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #2

Data used for an object detection ML system was found to have been labelled incorrectly in many cases.
Which ONE of the following options is most likely the reason for this problem?
SELECT ONE OPTION

  • A. Security issues
  • B. Bias issues
  • C. Privacy issues
  • D. Accuracy issues
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Question #3

A system was developed for screening the X-rays of patients for potential malignancy detection (skin cancer).
A workflow system has been developed to screen multiple cancers by using several individually trained ML models chained together in the workflow.
Testing the pipeline could involve multiple kind of tests (I - III):
I.Pairwise testing of combinations
II.Testing each individual model for accuracy
III.A/B testing of different sequences of models
Which ONE of the following options contains the kinds of tests that would be MOST APPROPRIATE to include in the strategy for optimal detection?
SELECT ONE OPTION

  • A. Only III
  • B. I and II
  • C. I and III
  • D. Only II
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #4

Which ONE of the following statements correctly describes the importance of flexibility for Al systems?
SELECT ONE OPTION

  • A. Flexible Al systems allow for easier modification of the system as a whole.
  • B. Al systems require changing of operational environments; therefore, flexibility is required.
  • C. Al systems are inherently flexible.
  • D. Self-learning systems are expected to deal with new situations without explicitly having to program for it.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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