Passing exam with CT-AI_v1.0_World latest training materials
Prepare and pass exam with our ISQI CT-AI_v1.0_World training material, here you will achieve your dream easily With TrainingQuiz!
Updated: Oct 15, 2026
No. of Questions: 40 Questions & Answers with Testing Engine
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ISQI CT-AI_v1.0_World Exam Overview:
| Certification Vendor: | iSQI / ISTQB |
|---|---|
| Exam Name: | ISTQB Certified Tester AI Testing (v1.0) |
| Exam Number: | CT-AI_v1.0_World |
| Real Exam Qty: | 40 |
| Exam Duration: | 60 (75 for non-native language) |
| Exam Price: | US$87.29 - US$213.00 / €240.00 (varies by region) |
| Exam Format: | Multiple Choice Questions (single/multiple answer) |
| Certificate Validity Period: | Lifetime |
| Available Languages: | Polish, English, French, German, Spanish, Brazilian Portuguese |
| Related Certifications: | ISTQB Certified Tester Foundation Level (CTFL) |
| Passing Score: | 65% (31 out of 47 points) |
| Recommended Training: | iSQI Training Partners ISTQB Accredited Training Providers |
| Exam Registration: | Pearson VUE iSQI Official Registration |
| Sample Questions: | ISQI CT-AI_v1.0_World Sample Questions |
| Exam Way: | In-person test center or online remote proctored (FLEX exam) |
| Pre Condition: | ISTQB Certified Tester Foundation Level (CTFL) certification required |
| Official Syllabus URL: | https://istqb.org/certifications/certified-tester-ai-testing-ct-ai-retiring/ |
ISQI CT-AI_v1.0_World Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Neural Networks and Testing | 4% | - Structure of neural networks - Coverage measures for deep learning |
| Testing Quality Characteristics | 11% | - Explainability and reliability testing - Testing transparency, fairness, robustness |
| Test Environment for AI Systems | 2% | - Data and infrastructure requirements |
| ML Data | 10% | - Data acquisition, preprocessing, labeling - Data quality issues and impact |
| Using AI for Testing Activities | 10% | - Test case generation, defect prediction - Regression optimization, test analysis |
| Testing AI-Based Systems | 11% | - Specific challenges and risks - Test strategy and approach |
| ML Functional Performance Metrics | 11% | - ROC, AUC, MSE, silhouette coefficient - Confusion matrix, accuracy, precision, recall |
| Machine Learning (ML) Overview | 11% | - Supervised, unsupervised, reinforcement learning - ML workflow, overfitting, underfitting |
| Quality Characteristics for AI-Based Systems | 10% | - Ethics, bias, transparency and safety - Flexibility, adaptability, autonomy |
| AI-Based System Testing Methods | 17% | - Model validation and verification - Adversarial testing, bias testing |
| Introduction to AI | 10% | - AI definitions and types
|
ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions:
A ML engineer is trying to determine the correctness of the new open-source implementation *X", of a supervised regression algorithm implementation. R-Square is one of the functional performance metrics used to determine the quality of the model.
Which ONE of the following would be an APPROPRIATE strategy to achieve this goal?
SELECT ONE OPTION
- A. Train various models by changing the order of input features and verify that the R-Square score of these models vary significantly.
- B. Drop 10% of the rows randomly and create another model and compare the R-Square scores of both the models.
- C. Add 10% of the rows randomly and create another model and compare the R-Square scores of both the model.
- D. Compare the R-Square score of the model obtained using two different implementations that utilize two different programming languages while using the same algorithm and the same training and testing data.
Correct Answer: D 🗳️
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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 quality of the labeling
- B. The data pipeline
- C. Biased data
- D. The number of classes
Correct Answer: D 🗳️
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ln the near future, technology will have evolved, and Al will be able to learn multiple tasks by itself without needing to be retrained, allowing it to operate even in new environments. The cognitive abilities of Al are similar to a child of 1-2 years.' In the above quote, which ONE of the following options is the correct name of this type of Al?
SELECT ONE OPTION
- A. Narrow Al
- B. Technological singularity
- C. Super Al
- D. General Al
Correct Answer: D 🗳️
Explanation: Only visible for TrainingQuiz members. You can sign-up / login (it's free).
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. Bias issues
- B. Security issues
- C. Privacy issues
- D. Accuracy issues
Correct Answer: D 🗳️
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