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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Fundamentals of Generative AI | 20% | - AI Terminology
|
| Topic 2: Testing Activities for Generative AI | 30% | - Requirements-Based Testing
|
| Topic 3: Tools for Testing Generative AI | 20% | - Testing Tools Overview
|
| Topic 4: Risks and Testing Challenges for Generative AI | 30% | - Testing Challenges for Generative AI
|
1. 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
2. What distinguishes an LLM-powered agent from a basic AI chatbot in test processes?
A) Ability to respond to prompts without explicit user instructions
B) Ability to trigger automated actions beyond conversation
C) Use of a conversational tone and improved response personalization
D) Reliance on predefined templates to generate short, factual answers
3. You are using an LLM to assist in analyzing test execution trends to predict potential risks. Which of the following improvements would BEST enhance the LLM's ability to predict risks and provide actionable alerts?
A) Emphasize constraints that focus on deviations that could impact release timelines or quality gates.
B) Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
C) Specify that the role is a test analyst with expertise in predictive analytics and risk management.
D) Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
4. Which setting can reduce variability by narrowing the sampling distribution during inference?
A) Using a larger context window
B) Increasing learning rate
C) Increasing temperature
D) Lowering temperature
5. What does an embedding represent in an LLM?
A) Logical rules for reasoning
B) Tokens grouped into context windows
C) Numerical vectors capturing semantic relationships
D) A set of test cases for validation
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: C |
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