ISQI CT-AI_v1.0_World Q&A - in .pdf

  • Exam Code: CT-AI_v1.0_World
  • Exam Name: ISTQB Certified Tester AI Testing (v1.0)
  • Updated: Jul 23, 2026
  • Q & A: 40 Questions and Answers
  • PDF Price: $59.98
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ISQI CT-AI_v1.0_World Q&A - Testing Engine

  • Exam Code: CT-AI_v1.0_World
  • Exam Name: ISTQB Certified Tester AI Testing (v1.0)
  • Updated: Jul 23, 2026
  • Q & A: 40 Questions and Answers
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ISQI CT-AI_v1.0_World Exam Syllabus Topics:
SectionObjectives
Topic 1: Quality Characteristics for AI-Based Systems- AI-Specific Quality Attributes
  • 1. Ethics
  • 2. Evolution
  • 3. Flexibility and Adaptability
  • 4. Bias
  • 5. Autonomy
  • 6. Transparency and Explainability
Topic 2: ML Functional Performance Metrics- Performance Evaluation
  • 1. Recall
  • 2. Accuracy
  • 3. F1 Score
  • 4. Precision
Topic 3: ML Data- Data Quality
  • 1. Data Preparation
  • 2. Data Bias
  • 3. Data Collection
Topic 4: Testing AI-Based Systems Overview- AI Testing Fundamentals
  • 1. Test Strategy
  • 2. AI Test Lifecycle
  • 3. Risk-Based Testing
Topic 5: Machine Learning- ML Fundamentals
  • 1. Training and Validation
  • 2. Supervised and Unsupervised Learning
  • 3. Machine Learning Overview
Topic 6: Methods and Techniques for Testing AI-Based Systems- Test Design Techniques
  • 1. Data-Oriented Testing
  • 2. Scenario-Based Testing
  • 3. Model Testing
Topic 7: Introduction to AI- AI Fundamentals
  • 1. AI Development Frameworks
  • 2. AI as a Service
  • 3. AI Technologies
  • 4. AI Definitions and Concepts
  • 5. AI-Based vs Conventional Systems
Topic 8: ML Neural Networks and Testing- Neural Networks
  • 1. Testing Neural Networks
  • 2. Neural Network Basics
Topic 9: Test Environments for AI-Based Systems- AI Test Infrastructure
  • 1. Monitoring and Maintenance
  • 2. Environment Configuration
  • 3. Data Management
Topic 10: Using AI for Testing- AI-Assisted Testing
  • 1. Defect Prediction
  • 2. Test Data Generation
  • 3. Test Automation Support
Topic 11: Testing AI-Specific Quality Characteristics- Quality Validation
  • 1. Explainability Assessment
  • 2. Robustness Testing
  • 3. Fairness Testing
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:

1. Written requirements are given in text documents, which ONE of the following options is the BEST way to generate test cases from these requirements?
SELECT ONE OPTION

A) Analyzing source code for generating test cases
B) GUI analysis by computer vision
C) Machine learning on logs of execution
D) Natural language processing on textual requirements


2. Upon testing a model used to detect rotten tomatoes, the following data was observed by the test engineer, based on certain number of tomato images.

For this confusion matrix which combinations of values of accuracy, recall, and specificity respectively is CORRECT?
SELECT ONE OPTION

A) 1,0.9, 0.8
B) 0.87.0.9. 0.84
C) 0.84.1,0.9
D) 1,0.87,0.84


3. Which ONE of the following options describes the LEAST LIKELY usage of Al for detection of GUI changes due to changes in test objects?
SELECT ONE OPTION

A) Using a vision-based detection of the GUI layout changes before and after test object changes.
B) Using a computer vision to compare the GUI before and after the test object changes.
C) Using a ML-based classifier to flag if changes in GUI are to be flagged for humans.
D) Using a pixel comparison of the GUI before and after the change to check the differences.


4. Which ONE of the following options describes a scenario of A/B testing the LEAST?
SELECT ONE OPTION

A) A comparison of two different websites for the same company to observe from a user acceptance perspective.
B) A comparison of the performance of an ML system on two different input datasets.
C) A comparison of two different offers in a recommendation system to decide on the more effective offer for same users.
D) A comparison of the performance of two different ML implementations on the same input data.


Solutions:

Question # 1
Answer: D
Question # 2
Answer: B
Question # 3
Answer: D
Question # 4
Answer: B

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