Q27 — AWS AIF-C01 Ch.2

Question 27 of 100 | ← Chapter 2

A company uses a foundation model (FM) from Amazon Bedrock to develop an enterprise search tool. The company wants to adapt the model using its own data to improve accuracy. Which strategy successfully adapts the model?

• A. Provide labeled data with prompt and completion fields. ✓
• B. Prepare the training dataset as a .txt file containing multiple lines of CSV-formatted content.
• C. Purchase preconfigured throughput for Amazon Bedrock.
• D. Train the model using journals and textbooks.

Correct Answer: A. Provide labeled data with prompt and completion fields.

Explanation

To successfully fine-tune an Amazon Bedrock foundation model, the key is training it on proprietary, domain-specific data aligned with business needs. Providing labeled data with explicit prompt and completion fields directly supports supervised fine-tuning, enabling the model to learn desired input-output mappings from the company’s data. This ensures tight alignment between training data and real-world application, effectively improving accuracy and utility.