- A
Use the Converse API to maintain conversation history
Why wrong: Conversation history does not ensure information freshness; it only helps with context.
- B
Use a smaller model like Amazon Titan Text Lite to reduce inference costs
A smaller model is cheaper per invocation and, when combined with RAG, can still provide accurate answers.
- C
Implement RAG by indexing the latest medical journals in a vector store
RAG enables retrieval of current information at inference time, ensuring responses are based on the latest research.
- D
Fine-tune a large model on the latest medical data monthly
Why wrong: Fine-tuning monthly is expensive and unnecessary when RAG can provide current information without retraining.
- E
Choose a model with the largest context window to include all research in the prompt
Why wrong: Including all research in the prompt is expensive, hits token limits, and is not scalable.
AIF-C01 Practice Question: A healthcare company is building a medical…
This AIF-C01 practice question tests your understanding of aif-c01 exam topics. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A healthcare company is building a medical diagnosis assistant using Amazon Bedrock. They need to ensure the model’s responses are based on the latest medical research and do not include outdated information. The company also wants to minimize costs. Which TWO actions should they take? (Select TWO)
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
Use a smaller model like Amazon Titan Text Lite to reduce inference costs
RAG allows the model to retrieve up-to-date information from a curated database without retraining. Using a smaller model like Titan Text Lite reduces cost. Fine-tuning would be expensive and still require updates. The Converse API does not ensure freshness. A large model with long context is costly.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use the Converse API to maintain conversation history
Why it's wrong here
Conversation history does not ensure information freshness; it only helps with context.
- ✓
Use a smaller model like Amazon Titan Text Lite to reduce inference costs
Why this is correct
A smaller model is cheaper per invocation and, when combined with RAG, can still provide accurate answers.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Implement RAG by indexing the latest medical journals in a vector store
Why this is correct
RAG enables retrieval of current information at inference time, ensuring responses are based on the latest research.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Fine-tune a large model on the latest medical data monthly
Why it's wrong here
Fine-tuning monthly is expensive and unnecessary when RAG can provide current information without retraining.
- ✗
Choose a model with the largest context window to include all research in the prompt
Why it's wrong here
Including all research in the prompt is expensive, hits token limits, and is not scalable.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which AIF-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this AIF-C01 question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Use a smaller model like Amazon Titan Text Lite to reduce inference costs — RAG allows the model to retrieve up-to-date information from a curated database without retraining. Using a smaller model like Titan Text Lite reduces cost. Fine-tuning would be expensive and still require updates. The Converse API does not ensure freshness. A large model with long context is costly.
What should I do if I get this AIF-C01 question wrong?
Identify which AIF-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
This AIF-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 AIF-C01 exam.
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