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ISQI CT-GenAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Deploying and Integrating GenAI in Test Organisations | 15% | - Strategy, governance, and adoption roadmap - Measuring value and continuous improvement - Roles, skills, and team readiness |
| Prompt Engineering for Effective Software Testing | 35% | - Iterative refinement and evaluation of prompts - Prompt patterns for test design, data generation, automation - Principles and structure of effective prompts |
| 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 |
| LLM-Powered Test Infrastructure | 10% | - AI agents and integration with test tools - Architecture and deployment considerations - 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 |
ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:
Question #1
Which AI approach requires feature engineering and structured data preparation?
A. Deep Learning
B. Generative AI
C. Classical Machine Learning
D. Symbolic AI
Question #2
Which statement BEST describes vision-language models (VLMs)?
A. VLMs are unrelated to multimodal LLMs and focus only on UI automation.
B. VLMs are a subset of multimodal LLMs integrating visual and textual information.
C. VLMs process audio and video but not images.
D. VLMs are a superset of multimodal LLMs.
Question #3
Which statement about fine-tuning for test tasks is INCORRECT?
A. It enhances relevance to organizational terminology and formats
B. It replaces the model's general knowledge entirely and prevents overfitting
C. It can be applied to smaller SLMs to improve task performance with lower compute
D. It adapts a pre-trained model to a domain using task-specific data
Question #4
Which concept refers to breaking text into smaller units for processing by LLMs?
A. Embeddings
B. Tokenization
C. Context Window
D. Transformer
Question #5
Which consideration BEST aligns LLM choice with organizational goals in a GenAI testing strategy?
A. Select open-source models prioritizing creativity over compliance or performance consistency
B. Select LLMs aligned to measurable test outcomes, compatible with current infrastructure
C. Select models with maximum vendor visibility and strong online presence to ensure reliability
D. Select broad-coverage models offering diverse functionalities for various test scenarios
Solutions:
| Question #1 Correct Answer: C | Question #2 Correct Answer: B | Question #3 Correct Answer: B | Question #4 Correct Answer: B | Question #5 Correct Answer: B |
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