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Amazon AIF-C01 Exam (page: 4)
Amazon AWS Certified AI Practitioner
Updated on: 25-Dec-2025

Viewing Page 4 of 43
AIF-C01 PDF 334 Questions

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?

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

Answer(s): A

Explanation:

Providing examples with labels in the prompt helps the LLM understand the context of sentiment analysis, improving its accuracy in classifying the new text passage as positive or negative. The other options do not effectively guide the LLM for sentiment analysis.



A security company is using Amazon Bedrock to run foundation models (FMs). The company wants to ensure that only authorized users invoke the models. The company needs to identify any unauthorized access attempts to set appropriate AWS Identity and Access Management (IAM) policies and roles for future iterations of the FMs.

Which AWS service should the company use to identify unauthorized users that are trying to access Amazon Bedrock?

  1. AWS Audit Manager
  2. AWS CloudTrail
  3. Amazon Fraud Detector
  4. AWS Trusted Advisor

Answer(s): B

Explanation:

AWS CloudTrail records API activity and provides a log of access attempts, which helps identify unauthorized users trying to access Amazon Bedrock. The other services are not specifically used for tracking unauthorized access attempts in this context.



A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model.

The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.

Which solution will meet these requirements?

  1. Use Amazon SageMaker Serverless Inference to deploy the model.
  2. Use Amazon CloudFront to deploy the model.
  3. Use Amazon API Gateway to host the model and serve predictions.
  4. Use AWS Batch to host the model and serve predictions.

Answer(s): A

Explanation:

Amazon SageMaker Serverless Inference allows the company to deploy the ML model without managing any underlying infrastructure, making it suitable for hosting the model and serving predictions. The other options do not directly provide serverless model deployment capabilities.



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?

  1. AWS Audit Manager
  2. AWS Artifact
  3. AWS Trusted Advisor
  4. AWS Data Exchange

Answer(s): B

Explanation:

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.



A company wants to use a large language model (LLM) to develop a conversational agent. The company needs to prevent the LLM from being manipulated with common prompt engineering techniques to perform undesirable actions or expose sensitive information.

Which action will reduce these risks?

  1. Create a prompt template that teaches the LLM to detect attack patterns.
  2. Increase the temperature parameter on invocation requests to the LLM.
  3. Avoid using LLMs that are not listed in Amazon SageMaker.
  4. Decrease the number of input tokens on invocations of the LLM.

Answer(s): A

Explanation:

Creating a prompt template that helps the LLM detect common attack patterns can reduce the risk of prompt injection and other undesirable manipulations. The other options do not effectively address the risk of prompt manipulation or unauthorized use.



A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix.

Which solution scope gives the company the MOST ownership of security responsibilities?

  1. Using a third-party enterprise application that has embedded generative AI features.
  2. Building an application by using an existing third-party generative AI foundation model (FM).
  3. Refining an existing third-party generative AI foundation model (FM) by fine-tuning the model by using data specific to the business.
  4. Building and training a generative AI model from scratch by using specific data that a customer owns.

Answer(s): D

Explanation:

Building and training a generative AI model from scratch gives the company the most ownership of security responsibilities, as it involves full control over data, training, deployment, and security measures. The other options involve varying levels of dependency on third-party tools and services, which reduces the company's ownership of security.



An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort.

Which strategy meets these requirements?

  1. Object detection
  2. Anomaly detection
  3. Named entity recognition
  4. Inpainting

Answer(s): A

Explanation:

Object detection is used to automatically identify and categorize objects (in this case, animals) in photos. It can detect the presence of animals and classify them accordingly. The other strategies are not suitable for identifying and categorizing animals in images.



A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment.

Which Amazon Bedrock pricing model meets these requirements?

  1. On-Demand
  2. Model customization
  3. Provisioned Throughput
  4. Spot Instance

Answer(s): A

Explanation:

The On-Demand pricing model provides flexibility without requiring a long-term commitment, allowing the company to pay only for the resources used, which fits well with a limited budget. The other options are either not relevant to pricing flexibility or involve specific resource commitments.



Viewing Page 4 of 43



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