MLS-C01 Machine Learning Implementation and Operations Practice Test 17 — 15 Questions

Question 1

A data scientist is using Amazon SageMaker to train a model and wants to use a custom Docker container for training. The container requires access to a private Amazon ECR repository. Which IAM role configuration is needed?

Accepted Answer

Attach an IAM policy to the SageMaker execution role that allows ecr:GetDownloadUrlForLayer, ecr:BatchGetImage, and ecr:GetAuthorizationToken for the ECR repository.. Option C is correct because the SageMaker execution role must have an IAM policy that allows ecr:GetDownloadUrlForLayer, ecr:BatchGetImage, and ecr:GetAuthorizationToken for the ECR repository. Option A is wrong because the ECR repository does not grant permissions to the SageMaker role via bucket policies. Option B is wrong because SageMaker does not use the ECR repository owner's role. Option D is wrong because the SageMaker role is the appropriate entity to grant permissions.

Answer

Use the AWS account owner's IAM role as the SageMaker execution role.

Answer

Create a new IAM user with ECR access and store credentials in SageMaker.

Answer

Add a bucket policy to the ECR repository allowing access from the SageMaker execution role.

Question 2

A company wants to use Amazon SageMaker to train a model using data that is updated daily. The training data is stored in an S3 bucket, and the team wants to automate the training process whenever new data arrives. Which AWS service should be used to trigger the SageMaker training job?

Accepted Answer

AWS Lambda triggered by S3 event notifications. Option B is correct because S3 events can trigger a Lambda function, which can then start the SageMaker training job. Option A is wrong because CloudWatch Events can schedule events but not directly triggered by S3 object creation. Option C is wrong because Step Functions can orchestrate the workflow but requires an S3 event to start. Option D is wrong because SQS is a queue service; it does not directly trigger Lambda from S3 events without additional setup.

Answer

Amazon CloudWatch Events

Answer

Amazon Simple Queue Service (SQS)

Answer

AWS Step Functions with a scheduled trigger

Question 3

A company is deploying a machine learning model on Amazon SageMaker. The model needs to be updated frequently with new versions. The team wants to minimize downtime and test the new model version before routing all traffic to it. Which TWO strategies should be used together?

Accepted Answer

Use Amazon SageMaker canary deployment.. Option A (blue/green deployment) and Option D (canary deployment) are correct. Blue/green allows a new version to be deployed alongside the old one, and canary deployment routes a small percentage of traffic to the new version for testing. Option B is wrong because A/B testing in SageMaker is typically done with production variants but does not inherently include canary routing; canary is a specific feature. Option C is wrong because rolling update is not a native SageMaker feature for endpoints. Option E is wrong because multi-model endpoints host multiple models but do not facilitate traffic shifting for updates.

Answer

Use a rolling update strategy.

Answer

Use a multi-model endpoint.

Answer

Use Amazon SageMaker A/B testing.

Question 4

A data scientist is training a model using Amazon SageMaker and wants to reduce the training time. The training job uses a single GPU instance. Which THREE actions can reduce training time?

Accepted Answer

Use distributed training across multiple GPU instances.. Options A, B, and D are correct. Using multiple GPUs (distributed training), using Pipe input mode, and using a larger instance type with more compute power can reduce training time. Option C is wrong because using more training data increases training time. Option E is wrong because reducing batch size can actually increase training time due to more iterations.

Answer

Increase the amount of training data.

Answer

Reduce the batch size.

Question 5

A company wants to deploy a machine learning model on Amazon SageMaker and needs to monitor the model's performance in production. Which TWO AWS services can be used to set up monitoring?

Accepted Answer

Amazon CloudWatch. Options A and D are correct. Amazon CloudWatch can monitor endpoint metrics, and SageMaker Model Monitor can detect data drift. Option B is wrong because AWS Config is for resource compliance, not model monitoring. Option C is wrong because Amazon Inspector is for security assessment. Option E is wrong because AWS X-Ray is for tracing requests, not model performance.

Answer

AWS X-Ray

Answer

Amazon Inspector

Answer

AWS Config

Question 6

A data scientist is deploying a PyTorch model to Amazon SageMaker for real-time inference. The model runs on a large instance but inference latency is too high. Which action is MOST likely to reduce latency without sacrificing accuracy?

Accepted Answer

Compile the model using SageMaker Neo. Option B is correct because SageMaker Neo optimizes trained models for target hardware, reducing latency without retraining. Option A may reduce latency but could affect accuracy. Option C changes instance type but not necessarily optimize the model. Option D changes endpoint type, not latency.

Answer

Switch from a GPU instance to a CPU instance

Answer

Quantize the model weights from FP32 to INT8

Answer

Deploy the model to a multi-model endpoint

Question 7

A team is using Amazon SageMaker to train a linear regression model on a dataset with 10 features. After training, they notice the model has high bias. Which action is MOST likely to reduce bias?

Accepted Answer

Add polynomial features to capture non-linear relationships. Option D is correct because high bias indicates underfitting, which can be reduced by adding more features or increasing model complexity. Option A reduces risk of overfitting, not bias. Option B increases regularization, which increases bias. Option C reduces data, potentially increasing bias.

Answer

Increase the regularization parameter lambda

Answer

Add L2 regularization

Answer

Use a smaller training dataset

Question 8

A machine learning engineer is using Amazon SageMaker to train a deep learning model. The training job is failing with a 'ResourceLimitExceeded' error. The engineer checks the account limits and sees that the current limit for the instance type is 2, and they are already using 2 instances for other jobs. Which approach would resolve the issue MOST cost-effectively?

Accepted Answer

Use a different instance type that is available and has sufficient capacity. Option B is correct because using a different instance type within the same family often has separate limits. Option A increases cost. Option C may not resolve if the limit is account-wide. Option D changes the request, not the limit.

Answer

Request a service limit increase for the current instance type

Answer

Use a managed spot training instead of on-demand

Answer

Stop the other training jobs to free up resources

Question 9

A data scientist is using Amazon SageMaker to train a model. The training job uses a custom Docker image stored in Amazon ECR. The training job fails with an error 'CannotPullContainerError'. Which TWO actions should the data scientist take to resolve this issue? (Choose TWO.)

Accepted Answer

Confirm that the image tag exists in the ECR repository. Options B and D are correct because checking ECR permissions and verifying the image tag are common causes. Option A is unrelated to pulling. Option C might be needed but not directly. Option E is irrelevant to the error.

Answer

Use a public Docker image instead of a custom one

Answer

Increase the training job timeout

Answer

Ensure the training instance has internet access

Question 10

A company is deploying a machine learning model using Amazon SageMaker. To reduce costs, they want to use SageMaker Managed Spot Training. Which THREE conditions must be met for the training job to use spot instances? (Choose THREE.)

Accepted Answer

The training job must be able to handle interruptions gracefully. Options A, C, and D are correct. Spot training requires checkpointing (A), the instance type must support spot (C), and the training job must be stoppable (D). Option B is not required — spot can be used in a VPC. Option E is not required; spot is only for training, not inference.

Answer

The model must be deployed to a serverless endpoint

Answer

The training job must be configured to run in a VPC

Question 11

A data engineer is building a data pipeline for a machine learning project using Amazon SageMaker. The raw data is stored in Amazon S3. Which TWO steps are essential to ensure data privacy and security before training? (Choose TWO.)

Accepted Answer

Encrypt the data at rest using S3 server-side encryption. Options B and E are correct because encryption at rest and in transit are essential. Option A is optional. Option C is for access control, but encryption is more fundamental. Option D is not a security measure.

Answer

Create a bucket policy that restricts access to the data scientist's IAM role only

Answer

Enable versioning on the S3 bucket

Answer

Use S3 Transfer Acceleration for faster uploads

Question 12

An IAM policy attached to a SageMaker execution role is shown in the exhibit. When a data scientist tries to create a training job that writes logs to CloudWatch Logs, the job fails. What is the MOST likely reason?

Accepted Answer

The policy lacks permissions for CloudWatch Logs actions. Option B is correct because the policy does not include CloudWatch Logs permissions. Option A is incorrect because the actions are allowed for all resources. Option C is incorrect because the S3 actions are allowed. Option D is incorrect because there is no deny statement.

Answer

The policy does not specify the SageMaker API version

Answer

The S3 bucket policy denies access to the training job

Answer

The policy has an implicit deny for SageMaker actions

Question 13

An engineer runs the AWS CLI command in the exhibit to create a SageMaker endpoint configuration. The endpoint is created successfully, but when invoked, the inference response is slow. The engineer wants to test with a different instance type. Which action should the engineer take?

Accepted Answer

Update the endpoint configuration with the new instance type and then update the endpoint. Option B is correct because updating the endpoint configuration and then updating the endpoint will apply the new instance type. Option A creates a new endpoint, not efficient. Option C does not change instance type. Option D is wrong because the endpoint can be updated.

Answer

Create a new endpoint configuration and use it to create a new endpoint

Answer

Modify the existing endpoint directly using the update-endpoint API with a new instance type parameter

Answer

Delete the endpoint and create a new one with the desired instance type

Question 14

An engineer sees the error in the exhibit when trying to deploy a model from a model registry in SageMaker. What is the MOST likely cause?

Accepted Answer

The model package version does not exist in the registry. Option A is correct because the error indicates the model package ARN does not exist. Option B would show a different error. Option C is not indicated. Option D would show a different error.

Answer

The IAM role lacks permission to access the model registry

Answer

The model package is still in 'Approved' status

Answer

The SageMaker endpoint is already deployed with the same model

Question 15

A data scientist creates a model resource in SageMaker using the JSON configuration in the exhibit. When creating an endpoint, the deployment fails with an error 'ModelError: Cannot find inference code'. What is the MOST likely cause?

Accepted Answer

The inference container environment does not specify SAGEMAKER_PROGRAM. Option D is correct because the inference container's Environment is empty; it should define SAGEMAKER_PROGRAM for the inference script. Option A is not necessarily missing. Option B would cause a different error. Option C is not required for inference.

Answer

The model.tar.gz file is missing the model weights

Answer

The ECR image does not exist

Answer

The training container does not have the SAGEMAKER_PROGRAM variable