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

ISQI CT-AI_v1.0_World Actual PDF
  • Exam Code: CT-AI_v1.0_World
  • Exam Name: ISTQB Certified Tester AI Testing (v1.0)
  • Updated: Aug 01, 2026
  • Q & A: 40 Questions and Answers
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About ISQI CT-AI_v1.0_World Exam

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ISQI CT-AI_v1.0_World Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Testing Quality Characteristics11%- Testing transparency, fairness, robustness
- Explainability and reliability testing
Topic 2: Introduction to AI10%- AI definitions and types
  • 1. AI vs conventional systems
    • 2. Narrow, General and Super AI
      - AI technologies and frameworks
      • 1. AI hardware and AIaaS
        Topic 3: Testing AI-Based Systems11%- Test strategy and approach
        - Specific challenges and risks
        Topic 4: Machine Learning (ML) Overview11%- Supervised, unsupervised, reinforcement learning
        - ML workflow, overfitting, underfitting
        Topic 5: Quality Characteristics for AI-Based Systems10%- Ethics, bias, transparency and safety
        - Flexibility, adaptability, autonomy
        Topic 6: Test Environment for AI Systems2%- Data and infrastructure requirements
        Topic 7: AI-Based System Testing Methods17%- Adversarial testing, bias testing
        - Model validation and verification
        Topic 8: Neural Networks and Testing4%- Structure of neural networks
        - Coverage measures for deep learning
        Topic 9: ML Data10%- Data quality issues and impact
        - Data acquisition, preprocessing, labeling
        Topic 10: Using AI for Testing Activities10%- Test case generation, defect prediction
        - Regression optimization, test analysis
        Topic 11: ML Functional Performance Metrics11%- ROC, AUC, MSE, silhouette coefficient
        - Confusion matrix, accuracy, precision, recall

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

        1. Which ONE of the following options does NOT describe a challenge for acquiring test data in ML systems?
        SELECT ONE OPTION

        A) Data for the use case is being generated at a fast pace.
        B) Test data being sourced from public sources.
        C) Nature of data constantly changes with lime.
        D) Compliance needs require proper care to be taken of input personal data.


        2. Which ONE of the following tests is MOST likely to describe a useful test to help detect different kinds of biases in ML pipeline?
        SELECT ONE OPTION

        A) Test the model during model evaluation for data bias.
        B) Testing the data pipeline for any sources for algorithmic bias.
        C) Testing the distribution shift in the training data for inappropriate bias.
        D) Check the input test data for potential sample bias.


        3. Arihant Meditation is a startup using Al to aid people in deeper and better meditation based on analysis of various factors such as time and duration of the meditation, pulse and blood pressure, EEG patters etc. among others. Their model accuracy and other functional performance parameters have not yet reached their desired level.
        Which ONE of the following factors is NOT a factor affecting the ML functional performance?
        SELECT ONE OPTION

        A) The data pipeline
        B) Biased data
        C) The quality of the labeling
        D) The number of classes


        4. Which ONE of the following options represents a technology MOST TYPICALLY used to implement Al?
        SELECT ONE OPTION

        A) Procedural programming
        B) Case control structures
        C) Search engines
        D) Genetic algorithms


        Solutions:

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

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