MLS-C01 Practice Test Questions – AWS Certified Machine Learning – Specialty

The AWS Certified Machine Learning – Specialty certification is intended for individuals who perform a development or data science role. It validates a candidate’s ability to design, implement, deploy, and maintain machine learning (ML) solutions for given business problems.

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MLS-C01 Practice Test Questions – AWS Certified Machine Learning – Specialty

1. A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive.

The model produces the following confusion matrix after evaluating on a test dataset of 100 customers:

Based on the model evaluation results, why is this a viable model for production?


2. A Machine Learning Specialist is designing a system for improving sales for a company. The objective is to use the large amount of information the company has on users’ behavior and product preferences to predict which products users would like based on the users’ similarity to other users.

What should the Specialist do to meet this objective?


3. A Mobile Network Operator is building an analytics platform to analyze and optimize a company’s operations using Amazon Athena and Amazon S3.

The source systems send data in .CSV format in real time. The Data Engineering team wants to transform the data to the Apache Parquet format before storing it on Amazon S3.

Which solution takes the LEAST effort to implement?


4. A city wants to monitor its air quality to address the consequences of air pollution. A Machine Learning Specialist needs to forecast the air quality in parts per million of contaminates for the next 2 days in the city. As this is a prototype, only daily data from the last year is available.

Which model is MOST likely to provide the best results in Amazon SageMaker?


5. A Data Engineer needs to build a model using a dataset containing customer credit card information

How can the Data Engineer ensure the data remains encrypted and the credit card information is secure?


6. A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance’s Amazon EBS volume, and needs to take a snapshot of that EBS volume.

However, the ML Specialist cannot find the Amazon SageMaker notebook instance’s EBS volume or Amazon EC2 instance within the VPC.

Why is the ML Specialist not seeing the instance visible in the VPC?


7. A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker. The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant.

Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test?


8. A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data

Which solution requires the LEAST effort to be able to query this data?


9. 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?


10. A Machine Learning Specialist has completed a proof of concept for a company using a small data sample, and now the Specialist is ready to implement an end-to-end solution in AWS using Amazon SageMaker. The historical training data is stored in Amazon RDS.

Which approach should the Specialist use for training a model using that data?


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