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ISQI CT-GenAI Exam Overview:
| Certification Vendor: | iSQI / ISTQB |
| Exam Name: | ISTQB Certified Tester Testing with Generative AI v1.0 |
| Exam Number: | CT-GenAI |
| Certificate Validity Period: | Lifetime |
| Real Exam Qty: | 40 |
| Exam Duration: | 60 (+25% for non-native language speakers) |
| Related Certifications: | ISTQB Certified Tester Foundation Level (CTFL) ISTQB Advanced Level Certifications ISTQB Expert Level Certifications |
| Passing Score: | 30 / 46 points (65%) |
| Available Languages: | English, German, Spanish, Portuguese, Chinese |
| Exam Price: | ~150 - 200 USD (varies by region) |
| Exam Format: | Multiple choice, Single / multiple correct answers, 1–2 points per question |
| Recommended Training: | ISTQB Accredited Training Providers |
| Exam Registration: | iSQI Official Registration |
| Sample Questions: | ISQI CT-GenAI Sample Questions |
| Exam Way: | Online remote proctored (iSQI FLEX) or in-person at test centres |
| Pre Condition: | Must hold ISTQB Certified Tester Foundation Level (CTFL) certification |
| Official Syllabus URL: | https://istqb.org/certifications/gen-ai/ |
ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prompt Engineering for Effective Software Testing | 35% | - Principles and structure of effective prompts - Iterative refinement and evaluation of prompts - Prompt patterns for test design, data generation, automation |
| Topic 2: Introduction to Generative AI for Software Testing | 15% | - Core concepts: Generative AI, LLMs, foundation models - Capabilities and limitations relevant to testing - Use cases across the testing lifecycle |
| Topic 3: Managing Risks of Generative AI in Software Testing | 25% | - Validation, verification, and mitigation strategies - Hallucinations, bias, inaccuracy, and consistency risks - Data privacy, security, and compliance concerns |
| Topic 4: Deploying and Integrating GenAI in Test Organisations | 15% | - Roles, skills, and team readiness - Measuring value and continuous improvement - Strategy, governance, and adoption roadmap |
| Topic 5: LLM-Powered Test Infrastructure | 10% | - RAG, fine-tuning, and model adaptation - AI agents and integration with test tools - Architecture and deployment considerations |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. Which competency MOST helps testers steer LLMs to produce useful, on-policy testware?
A) Configuring network routers
B) Designing custom CPU instructions
C) Mastering prompt engineering
D) Writing low-level device drivers
2. Which standard specifies requirements for managing AI systems within an organization, supporting consistent GenAI use in testing?
A) EU AI Act
B) NIST AI RMF 1.0
C) ISO/IEC 23053:2022
D) ISO/IEC 42001:2023
3. What defines a prompt pattern in the context of structured GenAI capability building?
A) Using ad hoc prompts without reference to previously proven structures or examples
B) Treating prompts as access credentials or compliance records rather than functional templates
C) Maintaining static documentation repositories without real-time prompt standardization processes
D) Applying a reusable and structured template that guides GenAI models toward consistent outputs
4. What is a hallucination in LLM outputs?
A) A logical mistake in multi-step deduction
B) Generation of factually incorrect content for the task
C) A systematic preference learned from data
D) A transient network failure during inference
5. Which statement BEST contrasts interaction style and scope?
A) Chatbots require API integration; LLM apps do not.
B) Both are identical aside from UI theme.
C) Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
D) Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: D |
By Evelyn
