AIP-C01 Practice Question: Foundation Model Integration Data And Compliance
A developer is designing a RAG system and wants to ensure high-quality retrieval. Which THREE techniques should be implemented to improve semantic search relevance?
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
✓
Using a reranking model to score retrieved documents
Hybrid search, reranking, and semantic chunking are standard best practices for enhancing RAG retrieval accuracy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Using a reranking model to score retrieved documents
Why this is correct
Reranking improves the relevance of the retrieved document set before generation.
- ✓
Applying semantic chunking based on document structure
Why this is correct
Semantic chunking keeps related information together better than fixed-size chunking.
- ✗
Increasing the vector dimension size to maximum
Why it's wrong here
Dimension size is fixed by the embedding model and doesn't directly dictate relevance.
- ✓
Implementing hybrid search combining keyword and vector search
Why this is correct
Hybrid search captures both lexical matches and semantic meaning.
- ✗
Using only fixed-size overlap chunking
Why it's wrong here
Fixed-size chunking often splits context, reducing retrieval quality.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Amazon Web Services exam blueprint
This AIP-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIP-C01 exam.