One purchase covers everything: a free demo to start, instant delivery, a support team that actually answers, 365 days of free updates, and a money back guarantee with clearly published conditions. That is the Prep4SureReview approach to the CTAT exam — 0 practice questions wrapped in a service built for the BICSI ISTQB Certified Tester AI Testing (CT-AI) V1.0 journey.
BICSI CTAT Exam Overview:
| Certification Vendor: | ISTQB (International Software Testing Qualifications Board) |
|---|---|
| Exam Name: | ISTQB Certified Tester AI Testing |
| Exam Number: | CT-AI v1.0 (CTAT) |
| Certificate Validity Period: | Lifetime; no periodic renewal required |
| Available Languages: | English |
| Exam Format: | Multiple-choice |
| Passing Score: | 31 out of 47 points (65%) |
| Real Exam Qty: | 40 |
| Exam Duration: | 60 (75 minutes for eligible candidates taking the exam in a non-native language) |
| Related Certifications: | ISTQB Certified Tester Foundation Level (CTFL) ISTQB Certified Tester Specialist ISTQB Certified Tester Advanced Level |
| Exam Way: | Exams may be taken through an accredited training provider, at an examination center, or in a public examination session. Online availability depends on the authorized examination provider. The English-language v1.0 exam is scheduled for retirement on April 21, 2027; non-English versions are scheduled for retirement on October 21, 2027. |
| Pre Condition: | ISTQB Certified Tester Foundation Level (CTFL) certification is required. Completion of an accredited training course is not mandatory. |
| Official Syllabus URL: | https://istqb.org/certifications/certified-tester-ai-testing-ct-ai-retiring/ |
BICSI CTAT Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Machine Learning Neural Networks and Testing | - Coverage Measures for Neural Networks - Neural Networks |
| Topic 2: Quality Characteristics for AI-Based Systems | - Safety and AI - Evolution - Bias - Side Effects and Reward Hacking - Ethics - Flexibility and Adaptability - Autonomy - Transparency, Interpretability and Explainability |
| Topic 3: Introduction to AI | - Narrow, General and Super AI - Pre-Trained Models
- Hardware for AI-Based Systems - AI-Based and Conventional Systems - AI Technologies - Definition of AI and AI Effect - AI as a Service (AIaaS)
|
| Topic 4: Test Environments for AI-Based Systems | - Virtual Test Environments for Testing AI-Based Systems - Test Environments for AI-Based Systems |
| Topic 5: Methods and Techniques for Testing AI-Based Systems | - Back-to-Back Testing - Pairwise Testing - Selecting Test Techniques for AI-Based Systems - Adversarial Attacks and Data Poisoning
- Experience-Based Testing of AI-Based Systems
|
| Topic 6: Using AI for Testing | - AI Technologies for Testing - Using AI for Testing User Interfaces
- Using AI for the Optimization of Regression Test Suites - Using AI for Defect Prediction - Using AI for Test Case Generation |
| Topic 7: Testing AI-Based Systems Overview | - Test Data for Testing AI-Based Systems - Specification of AI-Based Systems - Documenting an AI Component - Testing for Concept Drift - Testing for Automation Bias in AI-Based Systems - Selecting a Test Approach for an ML System - Test Levels for AI-Based Systems
|
| Topic 8: Testing AI-Specific Quality Characteristics | - Testing for Algorithmic, Sample and Inappropriate Bias - Challenges Testing Self-Learning Systems - Testing the Transparency, Interpretability and Explainability of AI-Based Systems - Testing Autonomous AI-Based Systems - Challenges Testing Probabilistic and Non-Deterministic AI-Based Systems - Test Oracles for AI-Based Systems - Challenges Testing Complex AI-Based Systems - Test Objectives and Acceptance Criteria |
| Topic 9: Machine Learning Functional Performance Metrics | - Limitations of ML Functional Performance Metrics - Additional ML Functional Performance Metrics for Classification, Regression and Clustering - Confusion Matrix - Benchmark Suites for ML - Selecting ML Functional Performance Metrics |
| Topic 10: Machine Learning (ML) Overview | - Overfitting and Underfitting
- Selecting a Form of ML - ML Workflow |
| Topic 11: Machine Learning Data | - Data Labelling for Supervised Learning
- Training, Validation and Test Datasets in the ML Workflow - Dataset Quality Issues |
Questions Candidates Ask About the BICSI ISTQB Certified Tester AI Testing (CT-AI) V1.0
The BICSI ISTQB Certified Tester AI Testing (CT-AI) V1.0 blueprint spans 11 domains. The heaviest hitters include Introduction to AI, Test Environments for AI-Based Systems, and Machine Learning Neural Networks and Testing. The complete breakdown — every domain and subtopic — is laid out in the syllabus section above, and that is the map your study sessions should follow.
Expect 40 questions and 60 (75 minutes for eligible candidates taking the exam in a non-native language) on the clock for the CTAT exam. Time management is a skill of its own here: candidates who untimed-study often discover the real pressure only when the countdown starts. Build that muscle memory early — run full timed simulations in the Prep4SureReview desktop or online test engine, practice flagging and skipping, and let pacing become reflex before exam day.
Delivery takes seconds, not days: your download is live immediately after checkout, and a copy reaches your email within one minute. If nothing lands within 2 hours, check the spam folder and message our support team. You may install the software on as many computers as you like — no device cap, ever.
If you sit the CTAT exam within 60 days of purchase and the result is a fail, the Prep4SureReview money back guarantee has you covered: file within 2 days of the exam with a scan of your enrollment slip and the official score report (PDF), and the claim is processed within 7 days. The candidate name must match the payer name; exams taken within 3 days of purchase, purchases never used in an actual attempt, free materials, and expired orders fall outside the policy. Not interested in a refund? Exchange the product for two free exam packages of equal value and keep the update service on your original purchase.
Formally known as the ISTQB Certified Tester AI Testing (CT-AI) V1.0, the CTAT exam is BICSI's way of certifying that you can apply its technologies to real-world problems — pass it, and you hold the BICSI Certification certification, a Specialist-level credential. Because it is vendor-backed and skills-driven, employers treat it as proof rather than promise. It also feeds into a wider path that includes ISTQB Certified Tester Foundation Level (CTFL), ISTQB Certified Tester Advanced Level, ISTQB Certified Tester Specialist.
There is — Prep4SureReview publishes a free PDF demo of the CTAT materials, so you can verify the accuracy and relevance of the questions before committing a cent. Buying unlocks 365 days of free updates on top of the full question bank, and if your product ever expires, the update service renews at a 50% discount from your member zone.
ISTQB Certified Tester Foundation Level (CTFL) certification is required. Completion of an accredited training course is not mandatory.
Requirements like these evolve, so before locking in an exam date, double-check the current rules on the official BICSI exam page.
