WGU D685 Practical Applications of Prompt Engineering |
100 Practice Questions and Answers with Rationales
(Objective Assessment Prep Guide)
1. What is the main goal of prompt engineering?
A. To train AI models
B. To design effective inputs that guide AI outputs
C. To reduce internet usage
D. To replace machine learning
Answer: B
Rationale: Prompt engineering focuses on crafting inputs (prompts) that improve AI
responses.
2. Which is an example of zero-shot prompting?
A. Giving examples before asking a question
B. Asking a question without examples
C. Fine-tuning a model
D. Training a dataset
Answer: B
Rationale: Zero-shot means no examples are provided to guide the model.
3. What is few-shot prompting?
A. Using no context
B. Using one instruction only
C. Providing examples in the prompt
D. Using multiple AI models
Answer: C
Rationale: Few-shot prompting includes examples to guide responses.
4. What is a hallucination in AI?
A. A visual error in graphics
B. When AI generates false or made-up information
,C. A system crash
D. A training dataset error
Answer: B
Rationale: Hallucination refers to incorrect or fabricated AI output.
5. What improves prompt effectiveness most?
A. Vague instructions
B. Clear and specific instructions
C. Shorter models
D. Random inputs
Answer: B
Rationale: Clarity reduces ambiguity and improves response quality.
6. What does “role prompting” do?
A. Changes hardware
B. Assigns a persona to the AI
C. Deletes data
D. Encrypts output
Answer: B
Rationale: Role prompting tells AI to respond as a specific expert or persona.
7. Which is a limitation of large language models?
A. Infinite memory
B. Always accurate responses
C. Lack of real-time understanding and possible errors
D. No need for training
Answer: C
Rationale: LLMs can generate incorrect or outdated information.
8. Temperature in AI controls:
A. Speed of hardware
B. Creativity/randomness of output
, C. Internet speed
D. Memory storage
Answer: B
Rationale: Higher temperature increases randomness and creativity.
9. What is prompt chaining?
A. One long prompt only
B. Breaking a task into multiple prompts
C. Removing prompts
D. Encrypting prompts
Answer: B
Rationale: Complex tasks are divided into steps using multiple prompts.
10. Which is best for factual accuracy?
A. High temperature prompts
B. Low temperature prompts
C. Random prompts
D. No prompts
Answer: B
Rationale: Low temperature reduces randomness and improves consistency.
11. What is bias in AI?
A. Hardware malfunction
B. Skewed or unfair outputs due to training data
C. Faster processing
D. Better accuracy
Answer: B
12. Which improves prompt clarity?
A. Ambiguous wording
B. Structured instructions
C. Shortcuts only
100 Practice Questions and Answers with Rationales
(Objective Assessment Prep Guide)
1. What is the main goal of prompt engineering?
A. To train AI models
B. To design effective inputs that guide AI outputs
C. To reduce internet usage
D. To replace machine learning
Answer: B
Rationale: Prompt engineering focuses on crafting inputs (prompts) that improve AI
responses.
2. Which is an example of zero-shot prompting?
A. Giving examples before asking a question
B. Asking a question without examples
C. Fine-tuning a model
D. Training a dataset
Answer: B
Rationale: Zero-shot means no examples are provided to guide the model.
3. What is few-shot prompting?
A. Using no context
B. Using one instruction only
C. Providing examples in the prompt
D. Using multiple AI models
Answer: C
Rationale: Few-shot prompting includes examples to guide responses.
4. What is a hallucination in AI?
A. A visual error in graphics
B. When AI generates false or made-up information
,C. A system crash
D. A training dataset error
Answer: B
Rationale: Hallucination refers to incorrect or fabricated AI output.
5. What improves prompt effectiveness most?
A. Vague instructions
B. Clear and specific instructions
C. Shorter models
D. Random inputs
Answer: B
Rationale: Clarity reduces ambiguity and improves response quality.
6. What does “role prompting” do?
A. Changes hardware
B. Assigns a persona to the AI
C. Deletes data
D. Encrypts output
Answer: B
Rationale: Role prompting tells AI to respond as a specific expert or persona.
7. Which is a limitation of large language models?
A. Infinite memory
B. Always accurate responses
C. Lack of real-time understanding and possible errors
D. No need for training
Answer: C
Rationale: LLMs can generate incorrect or outdated information.
8. Temperature in AI controls:
A. Speed of hardware
B. Creativity/randomness of output
, C. Internet speed
D. Memory storage
Answer: B
Rationale: Higher temperature increases randomness and creativity.
9. What is prompt chaining?
A. One long prompt only
B. Breaking a task into multiple prompts
C. Removing prompts
D. Encrypting prompts
Answer: B
Rationale: Complex tasks are divided into steps using multiple prompts.
10. Which is best for factual accuracy?
A. High temperature prompts
B. Low temperature prompts
C. Random prompts
D. No prompts
Answer: B
Rationale: Low temperature reduces randomness and improves consistency.
11. What is bias in AI?
A. Hardware malfunction
B. Skewed or unfair outputs due to training data
C. Faster processing
D. Better accuracy
Answer: B
12. Which improves prompt clarity?
A. Ambiguous wording
B. Structured instructions
C. Shortcuts only
