Microsoft AI-100 - Designing and Implementing an Azure AI Solution Exam
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Total 218 questions
Question #6 (Topic: Question Set 1)
You have an Azure Machine Learning model that is deployed to a web service.
You plan to publish the web service by using the name ml.contoso.com.
You need to recommend a solution to ensure that access to the web service is encrypted.
Which three actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
You plan to publish the web service by using the name ml.contoso.com.
You need to recommend a solution to ensure that access to the web service is encrypted.
Which three actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Generate a shared access signature (SAS)
B. Obtain an SSL certificate
C. Add a deployment slot
D. Update the web service
E. Update DNS
F. Create an Azure Key Vault
Answer: BDE
Question #7 (Topic: Question Set 1)
Your company recently deployed several hardware devices that contain sensors.
The sensors generate new data on an hourly basis. The data generated is stored on-premises and retained for several years.
During the past two months, the sensors generated 300 GB of data.
You plan to move the data to Azure and then perform advanced analytics on the data.
You need to recommend an Azure storage solution for the data.
Which storage solution should you recommend?
The sensors generate new data on an hourly basis. The data generated is stored on-premises and retained for several years.
During the past two months, the sensors generated 300 GB of data.
You plan to move the data to Azure and then perform advanced analytics on the data.
You need to recommend an Azure storage solution for the data.
Which storage solution should you recommend?
A. Azure Queue storage
B. Azure Cosmos DB
C. Azure Blob storage
D. Azure SQL Database
Answer: C
Question #8 (Topic: Question Set 1)
You plan to design an application that will use data from Azure Data Lake and perform sentiment analysis by using Azure Machine Learning algorithms.
The developers of the application use a mix of Windows- and Linux-based environments. The developers contribute to shared GitHub repositories.
You need all the developers to use the same tool to develop the application.
What is the best tool to use? More than one answer choice may achieve the goal.
The developers of the application use a mix of Windows- and Linux-based environments. The developers contribute to shared GitHub repositories.
You need all the developers to use the same tool to develop the application.
What is the best tool to use? More than one answer choice may achieve the goal.
A. Microsoft Visual Studio Code
B. Azure Notebooks
C. Azure Machine Learning Studio
D. Microsoft Visual Studio
Answer: C
Question #9 (Topic: Question Set 1)
You have several AI applications that use an Azure Kubernetes Service (AKS) cluster. The cluster supports a maximum of 32 nodes.
You discover that occasionally and unpredictably, the application requires more than 32 nodes.
You need to recommend a solution to handle the unpredictable application load.
Which scaling method should you recommend?
You discover that occasionally and unpredictably, the application requires more than 32 nodes.
You need to recommend a solution to handle the unpredictable application load.
Which scaling method should you recommend?
A. horizontal pod autoscaler
B. cluster autoscaler
C. manual scaling
D. Azure Container Instances
Answer: B
Question #10 (Topic: Question Set 1)
You deploy an infrastructure for a big data workload.
You need to run Azure HDInsight and Microsoft Machine Learning Server. You plan to set the RevoScaleR compute contexts to run rx function calls in parallel.
What are three compute contexts that you can use for Machine Learning Server? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
You need to run Azure HDInsight and Microsoft Machine Learning Server. You plan to set the RevoScaleR compute contexts to run rx function calls in parallel.
What are three compute contexts that you can use for Machine Learning Server? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. SQL
B. Spark
C. local parallel
D. HBase
E. local sequential
Answer: ABC
