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ISQI CT-GenAI Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Fundamentals of Generative AI	20%	- AI Development Lifecycle 1. Data collection, preparation, and curation 2. Model training and fine-tuning 3. Deployment and monitoring 4. Evaluation - Generative AI Concepts 1. Training data and context windows 2. Model types (Base, Instruction-tuned, RAG) 3. Emergent capabilities and limitations 4. Alignment and guardrails 5. AI model behavior 6. Hallucinations - AI Terminology 1. Generative AI (GenAI) 2. Deep Learning 3. Large Language Models (LLMs) 4. Artificial Intelligence (AI) 5. Transformer architecture 6. Machine Learning (ML) 7. Tokens and prompts
Topic 2: Risks and Testing Challenges for Generative AI	30%	- Testing Challenges for Generative AI 1. Complexity of the AI component 2. Subjectivity of quality assessment 3. Regulatory and compliance considerations 4. Non-deterministic output behavior 5. Coverage challenges 6. Test oracle problem 7. Ethical testing concerns - Quality Risks Specific to Generative AI 1. Input sensitivity (prompt brittleness) 2. Dependency on external components 3. Incorrect or fabricated outputs (hallucinations) 4. Inappropriate output for the context 5. Offensive, harmful, or biased content 6. Inconsistent responses across runs
Topic 3: Testing Activities for Generative AI	30%	- Traceability and Documentation 1. Documentation requirements for AI testing 2. Test coverage of AI model components - Model and Output Evaluation 1. Human evaluation methods 2. Output correctness and quality assessment 3. Checkpoint testing 4. Automated evaluation methods 5. Metamorphic testing - Prompt-Based Testing 1. Prompt engineering basics 2. Test case design using prompts 3. Test data creation with GenAI - Requirements-Based Testing 1. AI-related quality requirements 2. Functional requirements for AI-based systems 3. Non-functional requirements for AI-based systems
Topic 4: Tools for Testing Generative AI	20%	- Using Tools for Common Testing Activities 1. Security testing tools 2. Simulation and monitoring tools 3. Prompt testing tools 4. Model evaluation tools - Testing Tools Overview 1. Selecting appropriate tools for specific testing needs 2. Categories of GenAI testing tools

ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:

Question #1

What does an embedding represent in an LLM?

A. Logical rules for reasoning
B. A set of test cases for validation
C. Tokens grouped into context windows
D. Numerical vectors capturing semantic relationships

Reveal Solution Discussion 0

Correct Answer: D 🗳️