Free Practice Amazon MLA-C01 Exam Questions 2025

Stay ahead with 100% Free AWS Certified Machine Learning Engineer Associate MLA-C01 Dumps Practice Questions

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Total 254 Questions | Updated On: Mar 28, 2025

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Question 1

What is the first step in building a machine learning application?

A : Preparing the data

B : Training the model

C : Formulating the problem

D : Testing the model

Answer: C

Question 2

A Machine Learning Specialist is developing a custom video recommendation model for an application. The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket.The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance.Which approach allows the Specialist to use all the data to train the model?

A : Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset.

B : Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.

C : Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.

D : Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Train on a small amount of the data to verify the training code and hyperparameters. Go back to Amazon SageMaker and train using the full dataset.

Answer: C

Question 3

What is an indication that ML might be an overcomplicated solution?

A : The problem involves generating personalized responses.

B : The problem can be solved with traditional algorithms.

C : The problem involves complex and dynamic data.

D : The problem requires quick adaptation to new data.

Answer: B

Question 4

A company that promotes healthy sleep patterns by providing cloud-connected devices currently hosts a sleep tracking application on AWS.The application collects device usage information from device users.The company's Data Science team is building a machine learning model to predict if and when a user will stop utilizing the company's devices.Predictions from this model are used by a downstream application that determines the best approach for contacting users.The Data Science team is building multiple versions of the machine learning model to evaluate each version against the company's business goals.To measure long-term effectiveness, the team wants to run multiple versions of the model in parallel for long periods of time, with the ability to control the portion of inferences served by the models.Which solution satisfies these requirements with MINIMAL effort?

A : Build and host multiple models in Amazon SageMaker. Create an Amazon SageMaker endpoint configuration with multiple production variants. Programmatically control the portion of the inferences served by the multiple models by updating the endpoint configuration.

B : Build and host multiple models in Amazon SageMaker. Create a single endpoint that accesses multiple models. Use Amazon SageMaker batch transform to control invoking the different models through the single endpoint.

C : Build and host multiple models in Amazon SageMaker Neo to take into account different types of medical devices. Programmatically control which model is invoked for inference based on the medical device type.

D : Build and host multiple models in Amazon SageMaker. Create multiple Amazon SageMaker endpoints, one for each model. Programmatically control invoking different models for inference at the application layer.

Answer: B

Question 5

What is uncertainty in the context of machine learning?

A : The clarity of the model's decision-making process

B : The speed of the algorithm

C : The amount of data available for training

D : An imperfect outcome

Answer: D

Page: 1 / 51

Total 254 Questions | Updated On: Mar 28, 2025

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