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ISQI CT-GenAI Exam Syllabus Topics:

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

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

Question #1

Which concept refers to breaking text into smaller units for processing by LLMs?

A. Context Window
B. Tokenization
C. Embeddings
D. Transformer

Reveal Solution Discussion 0

Correct Answer: B 🗳️