Download AWS Certified AI Practitioner.AIF-C01.VCEplus.2024-09-09.47q.vcex

Vendor: Amazon
Exam Code: AIF-C01
Exam Name: AWS Certified AI Practitioner
Date: Sep 09, 2024
File Size: 29 KB
Downloads: 8
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Demo Questions

Question 1
A financial institution is using Amazon Bedrock to develop an AI application. The application is hosted in a VPC. To meet regulatory compliance standards, the VPC is not allowed access to any internet traffic.
Which AWS service or feature will meet these requirements?
  1. AWS PrivateLink
  2. Amazon Macie
  3. Amazon CloudFront
  4. Internet gateway
Correct answer: A
Question 2
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?
  1. Training
  2. Inference
  3. Model deployment
  4. Bias correction
Correct answer: B
Question 3
A company is using Amazon SageMaker Studio notebooks to build and train ML models. The company stores the data in an Amazon S3 bucket. The company needs to manage the flow of data from Amazon S3 to SageMaker Studio notebooks.
Which solution will meet this requirement?
  1. Use Amazon Inspector to monitor SageMaker Studio.
  2. Use Amazon Macie to monitor SageMaker Studio.
  3. Configure SageMaker to use a VPC with an S3 endpoint.
  4. Configure SageMaker to use S3 Glacier Deep Archive.
Correct answer: C
Question 4
A company is using domain-specific models. The company wants to avoid creating new models from the beginning. The company instead wants to adapt pre-trained models to create models for new, related tasks.
Which ML strategy meets these requirements?
  1. Increase the number of epochs.
  2. Use transfer learning.
  3. Decrease the number of epochs.
  4. Use unsupervised learning.
Correct answer: B
Question 5
A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source.
Which solution meets these requirements?
  1. Build a speech recognition system.
  2. Create a natural language processing (NLP) named entity recognition system.
  3. Develop an anomaly detection system.
  4. Create a fraud forecasting system.
Correct answer: C
Question 6
A student at a university is copying content from generative AI to write essays.
Which challenge of responsible generative AI does this scenario represent?
  1. Toxicity
  2. Hallucinations
  3. Plagiarism
  4. Privacy
Correct answer: C
Question 7
A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately.
Which Amazon SageMaker inference option will meet these requirements?
  1. Batch transform
  2. Real-time inference
  3. Serverless inference
  4. Asynchronous inference
Correct answer: A
Question 8
A company needs to choose a model from Amazon Bedrock to use internally. The company must identify a model that generates responses in a style that the company's employees prefer.
What should the company do to meet these requirements?
  1. Evaluate the models by using built-in prompt datasets.
  2. Evaluate the models by using a human workforce and custom prompt datasets.
  3. Use public model leaderboards to identify the model.
  4. Use the model InvocationLatency runtime metrics in Amazon CloudWatch when trying models.
Correct answer: B
Question 9
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.
Correct answer: D
Question 10
An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data.
How should the AI practitioner prevent responses based on confidential data?
  1. Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.
  2. Mask the confidential data in the inference responses by using dynamic data masking.
  3. Encrypt the confidential data in the inference responses by using Amazon SageMaker.
  4. Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).
Correct answer: A
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