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- Total Questions:120
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- Total Questions:120
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The complete CT-AI package: PDF to learn, simulator to validate. Know you're ready before ISTQB AI Testing exam day. Study anywhere, test anywhere. .
- Total Questions: 120 Q&A's
- Single Choice Questions: 119 Q&A's
- Multiple Choice Questions: 1 Q&A's
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Exams4sure has been helping working professionals since 2007 pass their certification exams on the first attempt, using less study time, less stress, and the most accurate CT-AI exam questions available.
Split your preparation the way the exam splits its marks
ISTQB CT-AI - ISTQB AI Testing Practice Exam
- Certification Provider:ISTQB
- Exam Code:CT-AI
- Exam Name:ISTQB Certified Tester AI Testing Exam
- Certification Name:ISTQB AI Testing
- Total Questions:120 Questions and Answers With Detailed Explanations
- Updated on:Based on the current CT-AI exam blueprint. Updated on Oct 4, 2026
- Product Format: PDF (Portable) & Test Engine (Interactive) .
- Support: 24/7 Live Chat & Email Support
- Valid For: Worldwide - Valid In All Countries
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- Updates: 90 Days of Free Content Updates.
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- Always Current & Accurate: Our content is continuously updated by ISTQB experts to align with the latest ISTQB AI Testing exam objectives. You study what's relevant.
- Master Every Question Type: Be prepared for the real thing with CT-AI practice questions covering Multiple Choice, HotSpot, Drag-and-Drop, and all other official exam formats.
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CT-AI Question and Answers
90% of ISTQB candidates pass within 2 weeks using only 30 minutes a day.
Get updated, verified CT-AI practice questions with detailed explanations. Start free today and see why thousands trust Exams4Sure.
A wildlife conservation group would like to use a neural network to classify images of different animals. The algorithm is going to be used on a social media platform to automatically pick out pictures of the chosen animal of the month. This month’s animal is set to be a wolf. The test team has already observed that the algorithm could classify a picture of a dog as being a wolf because of the similar characteristics between dogs and wolves. To handle such instances, the team is planning to train the model with additional images of wolves and dogs so that the model is able to better differentiate between the two.
What test method should you use to verify that the model has improved after the additional training?
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
“BioSearch” is creating an Al model used for predicting cancer occurrence via examining X-Ray images. The accuracy of the model in isolation has been found to be good. However, the users of the model started complaining of the poor quality of results, especially inability to detect real cancer cases, when put to practice in the diagnosis lab, leading to stopping of the usage of the model.
A testing expert was called in to find the deficiencies in the test planning which led to the above scenario.
Which ONE of the following options would you expect to MOST likely be the reason to be discovered by the test expert?
SELECT ONE OPTION
Stop the stress of unpredictable exam. Our CT-AI practice test is engineered to simulate the exact format, pacing, and pressure of the real ISTQB AI Testing exam. Go beyond simple ISTQB Certified Tester AI Testing Exam exam questions and answers; practice with CT-AI exam dumps in an interface that mirrors the actual ISTQB test, building the muscle memory and confidence you need to pass on your first try.
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Real Exam Simulation:
Our CT-AI practice exam interface is designed to look, feel, and function just like the real Pearson VUE testing software. From the timer countdown to the way you navigate between ISTQB Certified Tester AI Testing Exam exam questions, there will be no surprises on exam day.
Performance Analytics:
Get more than just a score. Receive a detailed breakdown of your performance by topic area. Identify your ISTQB AI Testing certification weak spots and focus your study efforts efficiently.
Verified & Updated Questions:
Our team of ISTQB experts continuously updates the question bank to ensure all content is relevant, accurate, and aligned with the latest CT-AI exam objectives.
Interactive Learning:
Read the explanation for every answer right or wrong. Understand the why behind each concept to solidify your ISTQB Certified Tester AI Testing Exam knowledge, not just memorize a answer.
Build Exam Stamina:
Taking our full-length, timed CT-AI practice test builds the mental endurance required to maintain focus and performance throughout the entire ISTQB AI Testing exam.
ISTQB CT-AI Detailed Exam Blueprint Structure
| Domain | Weightage |
|---|---|
| Introduction to AI | 9.1% |
| Quality Characteristics for AI | 9.1% |
| Machine Learning Foundations | 11.4% |
| Input Data Testing & Management | 13.6% |
| Model Testing & Performance Metrics | 22.7% |
| Advanced AI Testing Techniques | 22.7% |
| Testing Generative AI & LLMs | 11.4% |
CT-AI FAQs
It is a certification that validates knowledge of AI-based systems testing and AI techniques applied in software testing.
The exam is offered by ISTQB under the Certified Tester AI Testing (CT-AI) syllabus.
The exam consists of multiple-choice questions (MCQs).
Typically, the exam includes 40 multiple-choice questions.
The duration is 60 minutes, with an additional 25% time for non-native speakers (if applicable).
A minimum of 65% (26 correct answers out of 40) is required to pass.
It covers AI testing concepts, AI system risks, ML lifecycle, testing approaches, and AI tools.
The CT-AI certification is valid for life and does not expire.
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Focused exam prep made CT-AI certification straightforward for me
A perfect tool for busy professionals. The structure of the practice questions is efficient and mirrors the actual ISTQB exam format perfectly. It provided the boost I needed to sharpen my technical knowledge in AI testing.
