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?
⚠ Common exam trap
AI0-001 often tests the confusion between few-shot prompting (providing examples) and chain-of-thought prompting (eliciting reasoning steps) — candidates see 'step by step' and pick few-shot because both involve guiding the model, but only CoT explicitly structures the reasoning process.
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 (CoT) prompting explicitly instructs the model to reason through intermediate steps before producing a final answer, which is exactly what's needed for multi-step math problems. By asking the model to 'think step by step,' it decomposes the problem into manageable reasoning stages, significantly improving accuracy on arithmetic and logic tasks.
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 sampling randomness, not reasoning structure; 0.9 increases variability and worsens arithmetic reliability. It suits creative or divergent generation where varied outputs are wanted. Chain-of-thought prompting is required to produce the sequential reasoning steps the scenario demands.
- ✓
Chain-of-thought prompting
Why this is correct
Chain-of-thought prompting instructs the model to emit intermediate reasoning steps before the final answer, improving multi-step arithmetic accuracy. This directly satisfies the stem's requirement to solve a maths problem step by step rather than jumping to a result.
- ✗
Few-shot prompting
Why it's wrong here
Few-shot prompting supplies input-output examples, which shape format and style but do not explicitly elicit intermediate reasoning steps. It suits classification or formatting tasks with clear example patterns. Chain-of-thought prompting, by contrast, instructs the model to reason step by step before answering.
- ✗
Zero-shot prompting
Why it's wrong here
Zero-shot prompting supplies no worked reasoning examples, so the model answers directly and is prone to arithmetic slips on multi-step maths. It suits simple classification or extraction tasks where no reasoning chain is required. Chain-of-thought prompting, by contrast, elicits intermediate steps.
About these practice questions
Courseiva writes every AI0-001 question from scratch — 962 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.