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: Jan 29, 2026

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Question 1

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 2

An interactive online dictionary wants to add a widget that displays words used in similar contexts. A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget.

What should the Specialist do to meet these requirements?

A : eate one-hot word encoding vectors.

B : oduce a set of synonyms for every word using Amazon Mechanical Turk.

C : eate word embedding factors that store edit distance with every other word.

D : wnload word embedding's pre-trained on a large corpus.

Answer: D

Question 3

A Machine Learning Specialist built an image classification deep learning model. However the Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and 75%r respectively.

How should the Specialist address this issue and what is the reason behind it?

A : learning rate should be increased because the optimization process was trapped at a local minimum.

B : dropout rate at the flatten layer should be increased because the model is not generalized enough.

C : dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.

D : epoch number should be increased because the optimization process was terminated before it reached the global minimum.

Answer: D

Question 4

An office security agency conducted a successful pilot using 100 cameras installed at key locations within the main office. Images from the cameras were uploaded to Amazon S3 and tagged using Amazon Rekognition, and the results were stored in Amazon ES. The agency is now looking to expand the pilot into a full production system using thousands of video cameras in its office locations globally. The goal is to identify activities performed by non-employees in real time.

Which solution should the agency consider?

A : Use a proxy server at each local office and for each camera, and stream the RTSP feed to a uniqueAmazon Kinesis Video Streams video stream. On each stream, use Amazon Rekognition Video and createa stream processor to detect faces from a collection of known employees, and alert when non-employeesare detected.

B : Use a proxy server at each local office and for each camera, and stream the RTSP feed to a uniqueAmazon Kinesis Video Streams video stream. On each stream, use Amazon Rekognition Image to detectfaces from a collection of known employees and alert when non-employees are detected.

C : Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video toAmazon Kinesis Video Streams for each camera. On each stream, use Amazon Rekognition Video andcreate a stream processor to detect faces from a collection on each stream, and alert when nonemployeesare detected.

D : Install AWS DeepLens cameras and use the DeepLens_Kinesis_Video module to stream video toAmazon Kinesis Video Streams for each camera. On each stream, run an AWS Lambda function tocapture image fragments and then call Amazon Rekognition Image to detect faces from a collection ofknown employees, and alert when non-employees are detected.

Answer: C

Question 5

The displayed graph is from a foresting model for testing a time series.

Considering the graph only, which conclusion should a Machine Learning Specialist make about the behavior of the model?

A : model predicts both the trend and the seasonality well.

B : model predicts the trend well, but not the seasonality.

C : model predicts the seasonality well, but not the trend.

D : model does not predict the trend or the seasonality well.

Answer: D

Page: 1 / 79

Total 392 Questions | Updated On: Jan 29, 2026

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