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: Apr 01, 2026

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Question 1

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 2

A machine learning (ML) specialist is training a multilayer perceptron (MLP) on a dataset with multiple classes. The target class of interest is unique compared to the other classes in the dataset, but it does not achieve an acceptable recall metric. The ML specialist varies the number and size of the MLP's hidden layers, but the results do not improve significantly.

Which solution will improve recall in the LEAST amount of time?

A : Add class weights to the MLP's loss function, and then retrain.

B : Gather more data by using Amazon Mechanical Turk, and then retrain.

C : Train a k-means algorithm instead of an MLP.

D : Train an anomaly detection model instead of an MLP.

Answer: A

Question 3

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 4

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

Question 5

A data scientist receives a collection of insurance claim records. Each record includes a claim ID. the final outcome of the insurance claim, and the date of the final outcome.

The final outcome of each claim is a selection from among 200 outcome categories. Some claim records include only partial information. However, incomplete claim records include only 3 or 4 outcome categories from among the 200 available outcome categories. The collection includes hundreds of records for each outcome category. The records are from the previous 3 years.

The data scientist must create a solution to predict the number of claims that will be in each outcome category every month, several months in advance.

Which solution will meet these requirements?

A : Perform classification every month by using supervised learning of the 200 outcome categories based on claim contents.

B : Perform reinforcement learning by using claim IDs and dates. Instruct the insurance agents who submit the claim records to estimate the expected number of claims in each outcome category every month.

C : Perform forecasting by using claim IDs and dates to identify the expected number of claims in each outcome category every month.

D : Perform classification by using supervised learning of the outcome categories for which partial information on claim contents is provided. Perform forecasting by using claim IDs and dates for all other outcome categories.

Answer: C

Page: 1 / 79

Total 392 Questions | Updated On: Apr 01, 2026

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