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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering for Effective Software Testing | 35% | - Prompt patterns for test design, data generation, automation - Iterative refinement and evaluation of prompts - Principles and structure of effective prompts |
| 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 |
| LLM-Powered Test Infrastructure | 10% | - AI agents and integration with test tools - RAG, fine-tuning, and model adaptation - Architecture and deployment considerations |
| Deploying and Integrating GenAI in Test Organisations | 15% | - Roles, skills, and team readiness - Measuring value and continuous improvement - Strategy, governance, and adoption roadmap |
| Managing Risks of Generative AI in Software Testing | 25% | - Data privacy, security, and compliance concerns - Hallucinations, bias, inaccuracy, and consistency risks - Validation, verification, and mitigation strategies |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
1. What is a primary compliance concern related to Shadow AI in organizational test environments?
A) Violation of established data handling and regulatory compliance standards
B) Automated compliance validation during AI tool deployment
C) Failure to update system documentation within the test process
D) Difficulty in aligning project milestones with business outcomes
2. How do tester responsibilities MOSTLY evolve when integrating GenAI into test processes?
A) Moving from black-box exploratory testing toward exclusively performing code-based white-box checks
B) Transitioning from manual execution to complete automation with no human oversight
C) Replacing existing test coverage validation with automated summary reports generated by AI
D) Shifting from test execution toward reviewing, refining, and validating AI-generated testware
3. When an organization uses an AI chatbot for testing, what is the PRIMARY LLMOps concern?
A) Maximizing scalability by deploying larger cloud-based LLM clusters
B) Focusing primarily on user experience improvements and response formatting
C) Achieving faster responses by reducing model checkpoints and updates
D) Maintaining data privacy and minimizing security risks from external services
4. Which statement about fine-tuning for test tasks is INCORRECT?
A) It adapts a pre-trained model to a domain using task-specific data
B) It can be applied to smaller SLMs to improve task performance with lower compute
C) It replaces the model's general knowledge entirely and prevents overfitting
D) It enhances relevance to organizational terminology and formats
5. Which statement BEST contrasts interaction style and scope?
A) Both are identical aside from UI theme.
B) Chatbots enforce fixed workflows; LLM apps support free-form exploration beneficial for software testing
C) Chatbots enable conversational interactions; LLM apps provide capabilities for defined test tasks.
D) Chatbots require API integration; LLM apps do not.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: C | Question # 5 Answer: C |







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