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: Feb 19, 2026
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Question 1

A company is running a machine learning prediction service that generates 100 TB of predictions every day A Machine Learning Specialist must generate a visualization of the daily precision-recall curve from the predictions, and forward a read-only version to the Business team.
Which solution requires the LEAST coding effort?


Answer: C
Question 2

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.) 


Answer: B,C
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.) 


Answer: B,C
Question 4

A credit card company wants to build a credit scoring model to help predict whether a new credit card applicant
will default on a credit card payment. The company has collected data from a large number of sources with
thousands of raw attributes. Early experiments to train a classification model revealed that many attributes are
highly correlated, the large number of features slows down the training speed significantly, and that there are
some overfitting issues.
The Data Scientist on this project would like to speed up the model training time without losing a lot of
information from the original dataset.
Which feature engineering technique should the Data Scientist use to meet the objectives?


Answer: B
Question 5

n online delivery company wants to choose the fastest courier for each delivery at the moment an order is placed. The company wants to implement this feature for existing users and new users of its application. Data scientists have trained separate models with XGBoost for this purpose, and the models are stored in Amazon S3. There is one model for each city where the company operates.

Operation engineers are hosting these models in Amazon EC2 for responding to the web client requests, with one instance for each model, but the instances have only a 5% utilization in CPU and memory. The operation engineers want to avoid managing unnecessary resources.

Which solution will enable the company to achieve its goal with the LEAST operational overhead?


Answer: B
Page:    1 / 79      
Total 392 Questions | Updated On: Feb 19, 2026
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