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Amazon Web Services MLS-C01 Exam With Confidence Using Practice Dumps

Exam Code:
MLS-C01
Exam Name:
AWS Certified Machine Learning - Specialty
Certification:
Questions:
330
Last Updated:
May 28, 2026
Exam Status:
Stable
Amazon Web Services MLS-C01

MLS-C01: AWS Certified Specialty Exam 2025 Study Guide Pdf and Test Engine

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AWS Certified Machine Learning - Specialty Questions and Answers

Question 1

An Amazon SageMaker notebook instance is launched into Amazon VPC The SageMaker notebook references data contained in an Amazon S3 bucket in another account The bucket is encrypted using SSE-KMS The instance returns an access denied error when trying to access data in Amazon S3.

Which of the following are required to access the bucket and avoid the access denied error? (Select THREE)

Options:

A.

An AWS KMS key policy that allows access to the customer master key (CMK)

B.

A SageMaker notebook security group that allows access to Amazon S3

C.

An 1AM role that allows access to the specific S3 bucket

D.

A permissive S3 bucket policy

E.

An S3 bucket owner that matches the notebook owner

F.

A SegaMaker notebook subnet ACL that allow traffic to Amazon S3.

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Question 2

A wildlife research company has a set of images of lions and cheetahs. The company created a dataset of the images. The company labeled each image with a binary label that indicates whether an image contains a lion or cheetah. The company wants to train a model to identify whether new images contain a lion or cheetah.

.... Dh Amazon SageMaker algorithm will meet this requirement?

Options:

A.

XGBoost

B.

Image Classification - TensorFlow

C.

Object Detection - TensorFlow

D.

Semantic segmentation - MXNet

Question 3

A Mobile Network Operator is building an analytics platform to analyze and optimize a company's operations using Amazon Athena and Amazon S3

The source systems send data in CSV format in real lime The Data Engineering team wants to transform the data to the Apache Parquet format before storing it on Amazon S3

Which solution takes the LEAST effort to implement?

Options:

A.

Ingest .CSV data using Apache Kafka Streams on Amazon EC2 instances and use Kafka Connect S3 toserialize data as Parquet

B.

Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Glue to convert data into Parquet.

C.

Ingest .CSV data using Apache Spark Structured Streaming in an Amazon EMR cluster and use ApacheSpark to convert data into Parquet.

D.

Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Kinesis Data Firehose to convertdata into Parquet.