AWS Certified AI Practitioner AIF-C01 Practice Test

AWS Certified AI Practitioner AIF-C01 Practice Test practice questions, page 7 of 20, with answer review and explanations.

Question 31

A financial services company is using a generative AI (GenAI) model to create personalized investment summaries. The company is concerned about the model presenting convincing but factually incorrect financial information to customers. Which limitation of GenAI explains this concern?

  1. Limited access to real-time market data feeds without explicit integration
  2. Possibility of generating plausible-sounding but potentially false information
  3. Inability to automatically apply regulatory compliance frameworks without added controls
  4. Limited capability to personalize content for individual customers at scale

Question 32

A financial services company is deploying an AI customer support system to handle product inquiries. As the company adds new products and updates policies, the system must continue operating effectively without requiring rebuilding. Which AI characteristic is required for this use case?

  1. Consistency across interaction channels
  2. Adaptability to incorporate updated information
  3. Transparency in generating responses
  4. Reliability in handling high-volume requests

Question 33

A company is developing a customer service agent by using Amazon Bedrock. The company wants to ensure that the agent does not disclose personally identifiable information (PII) during conversations with users. Which Amazon Bedrock feature meets these requirements?

  1. Amazon Bedrock Guardrails
  2. Amazon Bedrock Flows
  3. Amazon Bedrock Knowledge Bases
  4. Amazon Bedrock Data Automation (BDA)

Question 34

A startup company is building a generative AI (GenAI) powered AI assistant on Amazon Bedrock. The company wants to minimize upfront costs and customize model responses for users. Which strategy will meet these requirements?

  1. Prompt engineering
  2. Fine-tuning
  3. Pre-training
  4. Retrieval Augmented Generation (RAG)

Question 35

A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts. An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders. What should the AI practitioner include in the report to meet the transparency and explainability requirements?

  1. Code for model training
  2. Partial dependence plots (PDPs)
  3. Sample data for training
  4. Model convergence tables