Amazon AIF-C01 Online Practice Questions and Exam Preparation

Amazon AIF-C01 Online Questions & Answers

• Question 31:

  HOTSPOT

  An ecommerce company is developing a generative AI solution to create personalized product recommendations for its application users. The company wants to track how effectively the AI solution increases product sales and user engagement in the application.

  Select the correct business metric from the following list for each business goal. Each business metric should be selected one time.

  

  

  Explanation:

  Measure how engaging the product recommendations are to users -> Click-through rate (CTR) Determine the effect of the AI solution on the total value of user purchases -> Average order value (AOV) Assess the AI solution's ability to encourage users to return to the platform -> Retention rate

  CTR reflects engagement with recommendations.

  AOV measures the impact on purchase value.

  Retention rate evaluates if users are returning due to the AI solution.

• Question 32:

  A company wants to use its documents as a knowledge base for a large language model (LLM) in a Retrieval Augmented Generation (RAG) solution.

  Which solution will meet these requirements?

  A. Encrypt each document with encryption keys.
  B. Create embeddings from document chunks.
  C. Label the document data with metadata.
  D. Generate one-hot encoding for each document
  B. Create embeddings from document chunks.

  ---

  Explanation

  In a RAG solution, documents are split into chunks and converted into embeddings so they can be indexed and retrieved based on semantic similarity to user queries.

• Question 33:

  A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to classify the sentiment of text passages as positive or negative. Which prompt engineering strategy meets these requirements?

  A. Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.
  B. Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt.
  C. Provide the new text passage to be classified without any additional context or examples.
  D. Provide the new text passage with a few examples of unrelated tasks, such as text summarization or question answering.
  A. Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.

  ---

  Providing examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified is the correct prompt engineering strategy for using a large language model (LLM) on Amazon Bedrock for sentiment analysis.

• Question 34:

  An AI practitioner is building an ML model. The AI practitioner wants to provide model transparency and explainability to stakeholders. Which solution will meet these requirements?

  A. Present the model Shapley values.
  B. Provide the model accuracy measure.
  C. Provide the model confusion matrix.
  D. Provide a secure model inference endpoint.
  A. Present the model Shapley values.

  ---

  Presenting the model Shapley values provides transparency and explainability by showing how each feature contributes to individual predictions, helping stakeholders understand the reasoning behind the model's outputs.

• Question 35:

  An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email message notifications when an ISV's compliance reports become available. Which AWS service can the company use to meet this requirement?

  A. AWS Audit Manager
  B. AWS Artifact
  C. AWS Trusted Advisor
  D. AWS Data Exchange
  B. AWS Artifact

  ---

  AWS Artifact provides access to compliance reports, including those from independent software vendors (ISVs). The company can use AWS Artifact to receive notifications when new compliance reports are available. The other services are not used for accessing and notifying about compliance reports.

• Question 36:

  A company wants to deploy a secure AI system with controlled access. The system must allow only authorized personnel to access model training data.

  Which AWS service will meet these requirements?

  A. AWS Key Management System (AWS KMS)
  B. Amazon EMR
  C. AWS Identity and Access Management (IAM)
  D. Amazon Redshift
  C. AWS Identity and Access Management (IAM)

  ---

  Explanation

  AWS Identity and Access Management (IAM) enables fine-grained access control by defining users, roles, and permissions, ensuring that only authorized personnel can access model training data.

• Question 37:

  A company uses Amazon Bedrock to implement a generative AI solution. The AI solution provides customers with personalized product recommendations.

  The company wants to evaluate the impact of the AI solution on sales revenue.

  Which metric will meet these requirements?

  A. Cross-domain performance
  B. Solution efficiency
  C. User satisfaction
  D. Conversion rate
  D. Conversion rate

  ---

  Explanation

  Conversion rate directly measures how often personalized recommendations lead to completed purchases, making it the most appropriate metric for evaluating the AI solution's impact on sales revenue.

• Question 38:

  A company wants to use a large language model (LLM) to generate product descriptions. The company wants to give the model example descriptions that follow a format. Which prompt engineering technique will generate descriptions that match the format?

  A. Zero-shot prompting
  B. Chain-of-thought prompting
  C. One-shot prompting
  D. Few-shot prompting
  D. Few-shot prompting

  ---

  Few-shot prompting provides the model with several example product descriptions that follow your desired format, enabling it to learn the pattern and generate new descriptions in the same style without further training.

• Question 39:

  A company wants to generate thousands of product images in various artistic styles using a generative model. The company needs fine control over style, texture, and detail. Which model type is MOST suitable?

  A. Transformer text model
  B. Diffusion model
  C. Embeddings model
  D. Instruction-following model
  B. Diffusion model

  ---

  Diffusion models excel at controlling visual detail, image style, and fidelity, making them ideal for high-quality image generation tasks in creative workflows.

• Question 40:

  Which large language model (LLM) parameter controls the number of possible next words or tokens considered at each step of the text generation process?

  A. Maximum tokens
  B. Top K
  C. Temperature
  D. Batch size
  B. Top K

  ---

  The TopK parameter limits token sampling at each generation step to the K most probable next tokens. By choosing how many of the highest-probability candidates to consider, TopK directly controls the breadth of options the model evaluates when generating each token.