microsoft ai-100 practice test

Designing and Implementing an Azure AI

Note: This exam has case studies

Question 1 Topic 3, Mixed Questions

You are developing an AI application for your company. The application will use Microsoft Azure Stream Analytics.
You save the outputs from the Stream Analytics workflows to the cloud.
Which of the following actions should you take?

  • A. Make use of a Hive table in Azure HDInsight
  • B. Make use of Azure Cosmos DB
  • C. Make use of Azure File storage
  • D. Make use of Azure Table storage
Answer:

C

Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-outputs

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Question 2 Topic 3, Mixed Questions

Your company is about to deploy an Azure Machine Learning experiment. The company is concerned that the experiment
might not be adhering to GDPR regulations.
You have been instructed to do a review of the experiment's adherence to GDPR regulations. You must perform the review
as quickly as possible.
Which of the following actions should you take?

  • A. Make use of Azure Policy
  • B. Make use of Azure Security Center
  • C. Make use of Azure Log Analytics
  • D. Make use of Compliance Manager
Answer:

D

Explanation:
Reference: https://azure.microsoft.com/en-us/blog/new-capabilities-to-enable-robust-gdpr-compliance/

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Question 3 Topic 3, Mixed Questions

You have developed an AI application for your company.
You want to prepare the application for deployment to Kubernetes.
Which three of the following actions should you perform? To answer, move the selected actions from the list of actions to the
answer area and rearrange them in the right order.
NOTE: Each correct selection is worth one point.
Select and Place:

Answer:

Explanation:
Reference: https://docs.microsoft.com/en-us/azure/aks/tutorial-kubernetes-prepare-app

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Question 4 Topic 3, Mixed Questions

You have deployed several Azure IoT Edge devices for an AI solution. The Azure IoT Edge devices generate measurement
data from temperature sensors.
You need a solution to process the sensor data. Your solution must be able to write configuration changes back to the
devices.
You make use of Azure Notification Hub.
Does this action accomplish your objective?

  • A. Yes, it does
  • B. No, it does not
Answer:

B

Explanation:
Use Microsoft Azure IoT Hub instead.
Reference:
https://azure.microsoft.com/en-us/resources/samples/functions-js-iot-hub-processing/

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Question 5 Topic 3, Mixed Questions

You have deployed several Azure IoT Edge devices for an AI solution. The Azure IoT Edge devices generate measurement
data from temperature sensors.
You need a solution to process the sensor data. Your solution must be able to write configuration changes back to the
devices.
You make use of Microsoft Azure Event Hub.
Does this action accomplish your objective?

  • A. Yes, it does
  • B. No, it does not
Answer:

B

Explanation:
Use Microsoft Azure IoT Hub instead.
Reference:
https://azure.microsoft.com/en-us/resources/samples/functions-js-iot-hub-processing/

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Question 6 Topic 3, Mixed Questions

You have deployed several Azure IoT Edge devices for an AI solution. The Azure IoT Edge devices generate measurement
data from temperature sensors.
You need a solution to process the sensor data. Your solution must be able to write configuration changes back to the
devices.
You make use of Microsoft Azure IoT Hub.
Does this action accomplish your objective?

  • A. Yes, it does
  • B. No, it does not
Answer:

A

Explanation:
Reference:
https://azure.microsoft.com/en-us/resources/samples/functions-js-iot-hub-processing/

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Question 7 Topic 3, Mixed Questions

You company's developers have created an Azure Data Factory pipeline that moves data from an on-premises server to
Azure Storage. The pipeline consumes Azure Cognitive Services APIs.
You need to deploy the pipeline. Your solution must minimize custom code.
You use Self-hosted Integration Runtime to move data to the cloud and Azure Logic Apps to consume Cognitive Services
APIs.
Does this action accomplish your objective?

  • A. Yes, it does
  • B. No, it does not
Answer:

A

Explanation:
A self-hosted Integration Runtime is capable of running copy activity between a cloud data stores and a data store in private
network.
Azure Logic Apps helps you orchestrate and integrate different services by providing 100+ ready-to-use connectors, ranging
from on-premises SQL Server or SAP to Microsoft Cognitive Services.
Reference: https://docs.microsoft.com/en-us/azure/data-factory/concepts-integration-runtime https://docs.microsoft.com/en-
us/azure/logic-apps/logic-apps-examples-and-scenarios

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Question 8 Topic 3, Mixed Questions

You are developing the workflow for an Azure Machine Learning solution. The solution must retrieve data from the following
on-premises sources:
Windows Server 2016 File servers
Microsoft SQL Server databases Oracle databases
Which of the following actions should you take?

  • A. Make use of Azure Data Factory to retrieve the data.
  • B. Make use of Azure Databricks to retrieve the data.
  • C. Make use of Azure Stream Analytics to retrieve the data.
  • D. Make use of Azure Synapse Analytics to retrieve the data.
Answer:

A

Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/use-data-from-an-on-premises-sql-server

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Question 9 Topic 3, Mixed Questions

You are designing an Azure Batch AI solution that will perform image recognition. The solution will be used to train several
Azure Machine Learning models.
You need to enable versioning for Azure Machine Learning models.
What should you do?

  • A. Register the Azure Machine Learning models.
  • B. Use Azure HDInsight cluster.
  • C. Use Machine Learning experiments.
  • D. Use Machine Learning pipelines.
Answer:

A

Explanation:
Model registration allows you to store and version your models in the Azure cloud, in your workspace. The model registry
makes it easy to organize and keep track of your trained models.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio/version-control https://docs.microsoft.com/en-
us/azure/machine-learning/how-to-deploy-and-where

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Question 10 Topic 3, Mixed Questions

You are developing an AI solution that will use in-memory caching and a columnar storage engine for Apache Hive queries.
What HDInsight platform should you use?

  • A. Apache Kafka
  • B. Apache Spark
  • C. Interactive Query
  • D. Apache Storm
Answer:

C

Explanation:
Interactive Query provides In-memory caching and improved columnar storage engine for Hive queries.
Reference:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/interactive-query/apache-interactive-query-get-started

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