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Fast2test is suitable for busy professional, who can know prepare for Certification exam in a week. Our CT-GenAI practice materials has been prepared by the team of ISQI experts after an in-depth analysis of vendor recommended syllabus. Now you can pass ISQI certification exam with our CT-GenAI study material on the first attempt.
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Our ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Preparation Material provides you everything you will need to take a ISQI AI Testing CT-GenAI examination. Details are researched and produced by ISQI Certification Experts who are constantly using industry experience to produce precise, and logical.
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Fast2test Practice Exams for ISQI AI Testing CT-GenAI are written to the highest standards of technical accuracy, using only certified subject matter experts and published authors for development.
ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Deploying and Integrating GenAI in Test Organisations | 15% | - Roles, skills, and team readiness - Strategy, governance, and adoption roadmap - Measuring value and continuous improvement |
| LLM-Powered Test Infrastructure | 10% | - Architecture and deployment considerations - AI agents and integration with test tools - RAG, fine-tuning, and model adaptation |
| Managing Risks of Generative AI in Software Testing | 25% | - Validation, verification, and mitigation strategies - Data privacy, security, and compliance concerns - Hallucinations, bias, inaccuracy, and consistency risks |
| Introduction to Generative AI for Software Testing | 15% | - Capabilities and limitations relevant to testing - Core concepts: Generative AI, LLMs, foundation models - Use cases across the testing lifecycle |
| Prompt Engineering for Effective Software Testing | 35% | - Principles and structure of effective prompts - Prompt patterns for test design, data generation, automation - Iterative refinement and evaluation of prompts |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern?
- A. Maintaining data privacy and minimizing security risks from external services
- B. Achieving faster responses by reducing model checkpoints and updates
- C. Focusing primarily on user experience improvements and response formatting
- D. Maximizing scalability by deploying larger cloud-based LLM clusters
Correct Answer: A 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
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 42001:2023
- D. ISO/IEC 23053:2022
Correct Answer: C 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
Which concept refers to breaking text into smaller units for processing by LLMs?
- A. Context Window
- B. Tokenization
- C. Transformer
- D. Embeddings
Correct Answer: B 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
Which factor MOST influences the overall energy consumption of a Generative AI model used in software testing tasks?
- A. The location of the data center determines model bias and accuracy levels
- B. The duration of user sessions primarily affects latency but not power efficiency
- C. The number of tokens processed directly determines the carbon intensity of each query
- D. The type of cloud platform affects processing speed but not total energy draw
Correct Answer: C 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
You must generate test cases for a new payments rule. The system includes API specifications stored in a vector database and prior tests in a relational database. Which of the following sequences BEST represents the correct order for applying a Retrieval-Augmented Generation (RAG) workflow?
i. Retrieve semantically similar specification chunks from the vector database ii. Feed both retrieved datasets as context for the LLM to generate new test cases iii. Retrieve relevant historical cases from the relational database iv. Submit a focused query describing the new test requirement
- A. i -> iv -> iii -> ii
- B. iv -> iii -> i -> ii
- C. iii -> iv -> i -> ii
- D. iv -> i -> iii -> ii
Correct Answer: D 🗳️
Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).
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