ISTQB CT-GenAI v1.1: 6 Practice Tests, 340 Questions

About this course

Prepare for the ISTQB CT-GenAI v1.1 — Certified Tester Testing with Generative AI certification with 6 practice tests and 340 challenging questions designed to strengthen your exam readiness.This course is built for learners who want more than simple recall questions. The practice tests use scenario-based questions, close answer choices, and detailed explanations to help you understand not just what the correct answer is, but why it is the most defensible answer in an exam-style situation.Generative AI is changing how software testing is performed. Testers are now expected to understand how large language models support test analysis, test design, test automation, test reporting, risk management, and organizational adoption. This course helps you practice those concepts through realistic testing scenarios.The course includes five deep syllabus-focused practice tests and one integrated mock exam:Practice Test 1 covers GenAI foundations for software testing, including LLMs, tokenization, embeddings, context windows, multimodal models, and AI chatbot interaction models.Practice Tests 2 and 3 cover prompt engineering in depth, including structured prompts, prompt chaining, few-shot prompting, meta prompting, system prompts, user prompts, test analysis, test design, test scripts, regression testing, monitoring, and GenAI output evaluation.Practice Test 4 focuses on GenAI risks, including hallucinations, reasoning errors, bias, non-deterministic behavior, data privacy, security risks, environmental impact, regulations, and standards.Practice Test 5 covers LLM-powered test infrastructure and organizational adoption, including RAG, vector databases, LLM-powered agents, fine-tuning, LLMOps, shadow AI, model selection, adoption roadmap, and change management.Practice Test 6 is a full integrated moc

Course objectives

• prepare effectively for the ISTQB CT-GenAI certification exam
• apply knowledge of generative AI in a testing context
• develop skills to design and analyze software tests using AI