Final Quiz: Generative AI: Prompt Engineering Basics :Generative AI: Prompt Engineering Basics (Generative AI for UI UX Design Specialization) Answers 2026

Question 1

Prompt engineering is primarily used to:

❌ Alter the model architecture
❌ Improve AI model memory retention
✅ Guide the AI’s responses by crafting strategic inputs
❌ Adjust training algorithms dynamically

Question 2

Which characteristic is most important in a well-constructed prompt?

❌ Number of examples provided
❌ Use of rare vocabulary
❌ Length and complexity
✅ Precision and relevance

Question 3

Which platform provides a web-based tool called “Playground” to experiment with GPT prompts?

✅ OpenAI
❌ IBM watsonx.ai
❌ Scale AI
❌ PromptPerfect

Question 4

CoT (Chain-of-Thought) prompting is most helpful for tasks involving:

❌ Predicting stock prices randomly
❌ Sentiment classification
❌ Translating simple sentences
✅ Structured reasoning and logic progression

Question 5

Tree-of-thought prompting differs from chain-of-thought prompting because it:

❌ Forces the model to converge on a single solution
❌ Prioritizes random generation
❌ Eliminates the need for prompts
✅ Encourages exploration of multiple potential paths simultaneously

Question 6

Which scenario best reflects a multimodal AI use case?

❌ Generating hashtags from a topic
✅ Creating a description based on an uploaded image
❌ Running sentiment analysis
❌ Writing a resume

Question 7

Which prompt best helps generate a clear, concise product description?

❌ “Give an overview of electronics.”
❌ “Write something nice about our latest launch.”
✅ “Create a short, feature-focused paragraph describing our waterproof smartwatch for fitness enthusiasts.”
❌ “Mention something about a gadget.”

Question 8

In IBM watsonx.ai Prompt Lab, which feature helps tailor prompts using task examples?

✅ Sample prompts for different use cases
❌ Domain-specific bias detection
❌ API integration
❌ AI-driven auto-completion

Question 9

Why choose the interview pattern approach?

❌ It minimizes prompt length
❌ It accelerates hallucination
✅ It helps guide the AI through structured, layered questioning
❌ It allows AI to ignore context

Question 10

Which text-to-image prompt is most likely to produce a high-quality, rich image?

❌ “A cardinal sitting on a branch in the snow with a faint light…”
✅ “Generate a hyper-realistic image of a red cardinal perched on a snow-covered pine branch during sunset.”
❌ “An image of a red cardinal standing on a snow-covered branch…”
❌ “A bird perched on a snowy tree branch…”

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