AIP-C01 Practice Question: Foundation Model Integration Data And Compliance
Which TWO factors are critical when choosing a model for a RAG architecture that requires high grounding accuracy?
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
✓
The model's support for citation and source attribution.
Accuracy in RAG relies on model reasoning capability and the quality of the retrieved chunks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model's training date.
Why it's wrong here
The training date is less important than the ability to follow retrieval-augmented instructions.
- ✗
The model's ability to generate images.
Why it's wrong here
Image generation is irrelevant to grounding accuracy in text-based RAG.
- ✓
The model's support for citation and source attribution.
Why this is correct
Citation capability is crucial for verifying the grounding of the model response.
- ✗
The number of parameters in the model.
Why it's wrong here
Parameter count does not directly translate to grounding accuracy.
- ✓
The context window size of the foundation model.
Why this is correct
Larger context windows allow for more retrieved information to be processed.
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.