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CT-GenAI exam is an important ISQI Certification which can test your professional skills. Candidates want to pass the exam successfully to prove their competence. Fast2test ISQI technical experts have collected and certified 42 questions and answers of AI Testing - ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 which are designed to cover the knowledge points of the Planning and Designing ISQI Superdome Server Solutions and enhance candidates' abilities. With Fast2test CT-GenAI preparation tests you can pass the AI Testing - ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 easily, get the ISQI certification and go further on ISQI career path.

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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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ISQI CT-GenAI Exam Syllabus Topics:

SectionWeightObjectives
Deploying and Integrating GenAI in Test Organisations15%- Roles, skills, and team readiness
- Strategy, governance, and adoption roadmap
- Measuring value and continuous improvement
LLM-Powered Test Infrastructure10%- Architecture and deployment considerations
- AI agents and integration with test tools
- RAG, fine-tuning, and model adaptation
Managing Risks of Generative AI in Software Testing25%- Validation, verification, and mitigation strategies
- Data privacy, security, and compliance concerns
- Hallucinations, bias, inaccuracy, and consistency risks
Introduction to Generative AI for Software Testing15%- Capabilities and limitations relevant to testing
- Core concepts: Generative AI, LLMs, foundation models
- Use cases across the testing lifecycle
Prompt Engineering for Effective Software Testing35%- 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
Reveal Solution  Discussion  0

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
Reveal Solution  Discussion  0

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
Reveal Solution  Discussion  0

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
Reveal Solution  Discussion  0

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
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

Explanation: Only visible for Fast2test members. You can sign-up / login (it's free).

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