AI0-001 Implementing AI Solutions Practice Question
A company wants to build a code generation tool that helps developers write Python functions. The tool must generate syntactically correct code. Which prompt engineering technique is MOST effective?
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
✓
Few-shot prompting with examples of valid Python functions
Few-shot examples showing valid Python function syntax help the model understand the expected output format and generate correct code.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Chain-of-thought prompting with step-by-step reasoning
Why it's wrong here
Chain-of-thought is more suited for reasoning tasks; for code generation, providing examples of correct code is more direct.
- ✗
System prompt instructing the model to output JSON
Why it's wrong here
JSON mode structures output but does not ensure syntactic correctness of the code itself.
- ✗
Instruction fine-tuning on a large Python corpus
Why it's wrong here
Fine-tuning is effective but requires extensive resources and data; prompt engineering is a lighter-weight solution.
- ✓
Few-shot prompting with examples of valid Python functions
Why this is correct
Few-shot examples demonstrate the expected syntax and structure, guiding the LLM to produce correct Python code.
About these practice questions
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.