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

When is unexplainability not acceptable?

A : When determining the result of a sports match

B : When making product recommendations

C : When explaining why a loan was declined

D : When explaining why a transaction was deemed fraudulent

Answer: C,D

Question 2

A machine learning specialist is developing a proof of concept for government users whose primary concern is security.The specialist is using Amazon SageMaker to train a convolutional neural network (CNN) model for a photo classifier application. The specialist wants to protect the data so that it cannot be accessed and transferred to a remote host by malicious code accidentally installed on the training container.Which action will provide the MOST secure protection?

A : Encrypt the weights of the CNN model.

B : Enable network isolation for training jobs.

C : Remove Amazon S3 access permissions from the SageMaker execution role.

D : Encrypt the training and validation dataset.

Answer: B

Question 3

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 4

A Machine Learning Specialist is implementing a full Bayesian network on a dataset that describes public transit in New York City.One of the random variables is discrete and represents the number of minutes New Yorkers wait for a bus given that the buses cycle every 10 minutes, with a mean of 3 minutes.Which prior probability distribution should the ML Specialist use for this variable?

A : Normal distribution

B : Poisson distribution

C : Uniform distribution

D : Binomial distribution

Answer: D

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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