ISQI CT-AI_v1.0_World - ISTQB Certified Tester AI Testing (v1.0)
- 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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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Testing Quality Characteristics | 11% | - Testing transparency, fairness, robustness - Explainability and reliability testing |
| Topic 2: Introduction to AI | 10% | - AI definitions and types
|
| Topic 3: Testing AI-Based Systems | 11% | - Test strategy and approach - Specific challenges and risks |
| Topic 4: Machine Learning (ML) Overview | 11% | - Supervised, unsupervised, reinforcement learning - ML workflow, overfitting, underfitting |
| Topic 5: Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
| Topic 6: Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| Topic 7: AI-Based System Testing Methods | 17% | - Adversarial testing, bias testing - Model validation and verification |
| Topic 8: Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| Topic 9: ML Data | 10% | - Data quality issues and impact - Data acquisition, preprocessing, labeling |
| Topic 10: Using AI for Testing Activities | 10% | - Test case generation, defect prediction - Regression optimization, test analysis |
| Topic 11: ML Functional Performance Metrics | 11% | - ROC, AUC, MSE, silhouette coefficient - Confusion matrix, accuracy, precision, recall |
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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