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ISTQB CT-AI v2.0 AI Testing Practice Exams | 240 Questions

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6 full mock exams on ML, GenAI, red teaming, input data and model testing, with detailed explanations for every option
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(60) Ratings
5 students
Created by Ahmed Alaa
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What you'll learn

  • Practice with 240 original questions in 6 full mock exams that follow the official ISTQB CT-AI v2.0 exam structure
  • Learn why every answer option is right or wrong, with explanations tied to each CT-AI v2.0 learning objective
  • Solve exam-style calculations on accuracy, precision, recall and F1, and apply metamorphic testing and dataset constraints
  • Check your readiness for each syllabus chapter, from ML basics and GenAI testing to input data, model and deployment testing
  • Build exam-day confidence by working through realistic 40-question, 60-minute practice tests until you pass consistently
This course includes:
240 questions on-demand video
0 articles
0 downloadable resources
0 lessons
Full lifetime access
Access on mobile and TV
Certificate of completion
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Course content

Requirements

  • ISTQB Certified Tester Foundation Level (CTFL) certification, which is required to sit the official CT-AI exam
  • Access to the free ISTQB CT-AI v2.0 syllabus, as these tests are designed to be used alongside it
  • No programming or data science experience is needed. Basic knowledge of software testing is enough to get started

Description

Preparing for the ISTQB® Certified Tester AI Testing (CT-AI) exam? This course gives you 6 full-length practice exams with 240 original questions, written from the new CT-AI v2.0 syllabus.

Every exam follows the official CT-AI v2.0 exam structure: 40 questions, 60 minutes, and the same mix of learning objectives and K-levels as the real exam. You practice exactly what the exam tests, chapter by chapter.

What makes these practice tests different:

– Written for v2.0 – covers the updated syllabus content, including generative AI testing, red teaming, data pipeline testing, data representativeness, label correctness, statistical ML performance testing and deployment testing.

– Every option explained – you learn why the correct answer is right AND why each wrong option is wrong, so every mistake becomes a lesson.

– Syllabus references – each question shows its learning objective (for example AI-5.1.5) and K-level, so you know exactly what to review.

– Exam-style calculations – practice confusion matrix metrics (accuracy, precision, recall, F1), dataset constraint scenarios and metamorphic testing questions like the K3 questions in the real exam.

– 100% original questions – no copied or reworded official sample questions.

Topics covered across all 6 exams:

1. Introduction to Artificial Intelligence

2. Quality Characteristics for AI-Based Systems

3. Machine Learning

4. Testing AI-Based Systems

5. Input Data Testing for Machine Learning Systems

6. Model Testing for Machine Learning Systems

7. Machine Learning Development Testing

Important note about scoring: the real CT-AI exam is points-based (44 points in total; K3 questions are worth 2 points, and you need 29 points to pass). Udemy scores every question equally, so aim for at least 70–75% here to build a safe margin for exam day.

How to use this course: take each exam in timed conditions, review every explanation, revisit the syllabus sections you missed, and retake the exam until you consistently score above the pass mark.

Disclaimer: This course is not affiliated with, endorsed by, or sponsored by ISTQB®. ISTQB® is a registered trademark of the International Software Testing Qualifications Board.

Who this course is for:

  • Software testers and QA engineers preparing for the ISTQB CT-AI v2.0 (AI Testing) certification exam
  • CTFL-certified testers who want to move into testing AI-based and machine learning systems
  • Test leads, developers and data professionals who need a structured way to check their understanding of AI testing concepts
  • Candidates who studied the older CT-AI v1.0 syllabus and want practice aligned with the updated v2.0 content
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