AMAZON LATEST AIF-C01 LEARNING MATERIALS: AWS CERTIFIED AI PRACTITIONER - ACTUALTESTSQUIZ PASS-LEADING PROVIDER

Amazon Latest AIF-C01 Learning Materials: AWS Certified AI Practitioner - ActualTestsQuiz Pass-leading Provider

Amazon Latest AIF-C01 Learning Materials: AWS Certified AI Practitioner - ActualTestsQuiz Pass-leading Provider

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Tags: Latest AIF-C01 Learning Materials, Test AIF-C01 Quiz, Valid AIF-C01 Study Notes, Valid AIF-C01 Exam Sims, AIF-C01 Updated Test Cram

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Amazon AWS Certified AI Practitioner Sample Questions (Q56-Q61):

NEW QUESTION # 56
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?

  • A. AWS Audit Manager
  • B. AWS Trusted Advisor
  • C. AWS CloudTrail
  • D. Amazon Fraud Detector

Answer: C


NEW QUESTION # 57
A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality.
Which action must the company take to use the custom model through Amazon Bedrock?

  • A. Purchase Provisioned Throughput for the custom model.
  • B. Grant access to the custom model in Amazon Bedrock.
  • C. Register the model with the Amazon SageMaker Model Registry.
  • D. Deploy the custom model in an Amazon SageMaker endpoint for real-time inference.

Answer: D

Explanation:
To use a custom model that has been trained to improve summarization quality, the company must deploy the model on an Amazon SageMaker endpoint. This allows the model to be used for real-time inference through Amazon Bedrock or other AWS services. By deploying the model in SageMaker, the custom model can be accessed programmatically via API calls, enabling integration with Amazon Bedrock.
Option B (Correct): "Deploy the custom model in an Amazon SageMaker endpoint for real-time inference":
This is the correct answer because deploying the model on SageMaker enables it to serve real-time predictions and be integrated with Amazon Bedrock.
Option A: "Purchase Provisioned Throughput for the custom model" is incorrect because provisioned throughput is related to database or storage services, not model deployment.
Option C: "Register the model with the Amazon SageMaker Model Registry" is incorrect because while the model registry helps with model management, it does not make the model accessible for real-time inference.
Option D: "Grant access to the custom model in Amazon Bedrock" is incorrect because Bedrock does not directly manage custom model access; it relies on deployed endpoints like those in SageMaker.
AWS AI Practitioner References:
Amazon SageMaker Endpoints: AWS recommends deploying models to SageMaker endpoints to use them for real-time inference in various applications.


NEW QUESTION # 58
Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?

  • A. Assess the color accuracy of images processed by the model.
  • B. Measure the model's accuracy against a predefined benchmark dataset.
  • C. Count the number of layers in the neural network.
  • D. Calculate the total cost of resources used by the model.

Answer: B

Explanation:
Measuring the model's accuracy against a predefined benchmark dataset is the correct strategy to evaluate the accuracy of a foundation model (FM) used in image classification tasks.
* Model Accuracy Evaluation:
* In image classification, the accuracy of a model is typically evaluated by comparing the predicted labels with the true labels in a benchmark dataset that is representative of the real-world data the model will encounter.
* This approach provides a quantifiable measure of how well the model performs on known data and is a standard practice in machine learning.
* Why Option B is Correct:
* Benchmarking Accuracy: Using a predefined dataset allows for consistent and reliable evaluation of model performance.
* Standard Practice: It is a widely accepted method for assessing the effectiveness of image classification models.
* Why Other Options are Incorrect:
* A. Total cost of resources: Does not measure model accuracy but rather the cost of operation.
* C. Number of layers in the neural network: Does not directly correlate with the accuracy or performance of the model.
* D. Color accuracy of images processed by the model: Is unrelated to the model's classification accuracy.


NEW QUESTION # 59
A company wants to create a chatbot by using a foundation model (FM) on Amazon Bedrock. The FM needs to access encrypted data that is stored in an Amazon S3 bucket.
The data is encrypted with Amazon S3 managed keys (SSE-S3).
The FM encounters a failure when attempting to access the S3 bucket data.
Which solution will meet these requirements?

  • A. Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key.
  • B. Set the access permissions for the S3 buckets to allow public access to enable access over the internet.
  • C. Use prompt engineering techniques to tell the model to look for information in Amazon S3.
  • D. Ensure that the S3 data does not contain sensitive information.

Answer: A

Explanation:
Amazon Bedrock needs the appropriate IAM role with permission to access and decrypt data stored in Amazon S3. If the data is encrypted with Amazon S3 managed keys (SSE-S3), the role that Amazon Bedrock assumes must have the required permissions to access and decrypt the encrypted data.
* Option A (Correct): "Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key": This is the correct solution as it ensures that the AI model can access the encrypted data securely without changing the encryption settings or compromising data security.
* Option B: "Set the access permissions for the S3 buckets to allow public access" is incorrect because it violates security best practices by exposing sensitive data to the public.
* Option C: "Use prompt engineering techniques to tell the model to look for information in Amazon S3" is incorrect as it does not address the encryption and permission issue.
* Option D: "Ensure that the S3 data does not contain sensitive information" is incorrect because it does not solve the access problem related to encryption.
AWS AI Practitioner References:
* Managing Access to Encrypted Data in AWS: AWS recommends using proper IAM roles and policies to control access to encrypted data stored in S3.


NEW QUESTION # 60
A company built a deep learning model for object detection and deployed the model to production.
Which AI process occurs when the model analyzes a new image to identify objects?

  • A. Model deployment
  • B. Training
  • C. Bias correction
  • D. Inference

Answer: D


NEW QUESTION # 61
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