Free Amazon MLS-C01 Exam Questions

Become Amazon Certified with updated MLS-C01 exam questions and correct answers

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Total 392 Questions | Updated On: Mar 06, 2026

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Question 1

A Machine Learning Specialist needs to create a data repository to hold a large amount of time-based training data for a new model. In the source system, new files are added every hour Throughout a single 24-hour period, the volume of hourly updates will change significantly. The Specialist always wants to train on the last 24 hours of the data

Which type of data repository is the MOST cost-effective solution?

A : Amazon EBS-backed Amazon EC2 instance with hourly directories

B : Amazon RDS database with hourly table partitions

C : Amazon S3 data lake with hourly object prefixes

D : Amazon EMR cluster with hourly hive partitions on Amazon EBS volumes

Answer: C

Question 2

A company is training machine learning (ML) models on Amazon SageMaker by using 200 TB of data that is stored in Amazon S3 buckets. The training data consists of individual files that are each larger than 200 MB in size. The company needs a data access solution that offers the shortest processing time and the least amount of setup. Which solution will meet these requirements?

A : File mode in SageMaker to copy the dataset from the S3 buckets to the ML instance storage.

B : eate an Amazon FSx for Lustre file system. Link the file system to the S3 buckets.

C : eate an Amazon Elastic File System (Amazon EFS) file system. Mount the file system to the training instances

D : FastFile mode in SageMaker to stream the files on demand from the S3 buckets

Answer: D

Question 3

A data scientist is building a new model for an ecommerce company. The model will predict how many minutes it will take to deliver a package. During model training, the data scientist needs to evaluate model performance. Which metrics should the data scientist use to meet this requirement? (Select TWO.)

A : InferenceLatency

B : Mean squared error (MSE)

C : Root mean squared error (RMSE)

D : Precision

E : Accuracy

Answer: B,C

Question 4

Amazon Connect has recently been tolled out across a company as a contact call center The solution has been configured to store voice call recordings on Amazon S3

The content of the voice calls are being analyzed for the incidents being discussed by the call operators Amazon Transcribe is being used to convert the audio to text, and the output is stored on Amazon S3

Which approach will provide the information required for further analysis?

A : Amazon Comprehend with the transcribed files to build the key topics

B : Amazon Translate with the transcribed files to train and build a model for the key topics

C : Use the AWS Deep Learning AMI with Gluon Semantic Segmentation on the transcribed files to train and build a model for the key topics

D : the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the transcribed files to generate a word embeddings dictionary for the key topics

Answer: B

Question 5

A bank's Machine Learning team is developing an approach for credit card fraud detection The company has a large dataset of historical data labeled as fraudulent The goal is to build a model to take the information from new transactions and predict whether each transaction is fraudulent or not

Which built-in Amazon SageMaker machine learning algorithm should be used for modeling this problem?

A : q2seq

B : Boost

C : means

D : ndom Cut Forest (RCF)

Answer: C

Page: 1 / 79

Total 392 Questions | Updated On: Mar 06, 2026

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