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AI Concepts and TechniquesmediumMultiple ChoiceObjective-mapped

AI0-001 AI Concepts and Techniques Practice Question

A developer is using a large language model via an API. They want the model to solve a math problem step by step. Which prompt engineering technique should they use?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Chain-of-thought prompting

Chain-of-thought prompting encourages the model to show intermediate reasoning steps, improving accuracy on multi-step problems. Zero-shot gives no examples; few-shot provides examples but not necessarily step-by-step; temperature controls randomness.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Set temperature to 0.9

    Why it's wrong here

    Temperature controls randomness, not reasoning structure; high temperature may reduce accuracy.

  • Chain-of-thought prompting

    Why this is correct

    Chain-of-thought prompts the model to output intermediate reasoning steps, which improves performance on arithmetic and logic problems.

  • Few-shot prompting

    Why it's wrong here

    Few-shot provides examples but does not explicitly encourage step-by-step reasoning unless the examples include it.

  • Zero-shot prompting

    Why it's wrong here

    Zero-shot gives no guidance on reasoning steps, often leading to incorrect answers for complex math.

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