Amazon Web Services AWS Certified AI Practitioner Exam AIF-C01 Question # 106 Topic 11 Discussion
AIF-C01 Exam Topic 11 Question 106 Discussion:
Question #: 106
Topic #: 11
A company has developed an ML model to predict real estate sale prices. The company wants to deploy the model to make predictions without managing servers or infrastructure.
Which solution meets these requirements?
A.
Deploy the model on an Amazon EC2 instance.
B.
Deploy the model on an Amazon Elastic Kubernetes Service (Amazon EKS) cluster.
C.
Deploy the model by using Amazon CloudFront with an Amazon S3 integration.
D.
Deploy the model by using an Amazon SageMaker AI endpoint.
Amazon SageMaker endpoints provide fully managed, serverless model deployment for real-time and batch predictions, allowing companies to deploy ML models without handling any servers or infrastructure management.
D is correct: SageMaker endpoints let you deploy, scale, and monitor ML models with no infrastructure overhead.
A and B require infrastructure management.
C (CloudFront/S3) is not for model deployment, but for static content delivery.
“Amazon SageMaker endpoints allow you to deploy machine learning models for inference without the need to manage underlying infrastructure.”
(Reference: AWS SageMaker Model Deployment, AWS Certified AI Practitioner Study Guide)
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