Microsoft Microsoft Certifications AI-100 Questions & Answers

• Question 21:

  Your company has an Azure subscription that contains an Azure Active Directory (Azure AD) tenant.

  Azure AD contains 500 user accounts for your company's employees. Some temporary employees do NOT have user accounts in Azure AD.

  You are designing a storage solution for video files and metadata files.

  You plan to deploy an application to perform analysis of the metadata files.

  You need to recommend an authentication solution to provide links to the video files. The solution must provide access to each file for only five minutes.

  What should you include in the recommendation?

  A. Secondary Storage Key

  B. Primary Storage Key

  C. Shared Access Signature

  D. Azure Active Directory

  Correct Answer: C

  References: https://docs.microsoft.com/en-us/azure/storage/common/storage-dotnet-shared-access-signature-part-1

• Question 22:

  Your company plans to implement an AI solution that will analyze data from IoT devices.

  Data from the devices will be analyzed in real time. The results of the analysis will be stored in a SQL database.

  You need to recommend a data processing solution that uses the Transact-SQL language.

  Which data processing solution should you recommend?

  A. Azure Stream Analytics

  B. SQL Server Integration Services (SSIS)

  C. Azure Event Hubs

  D. Azure Machine Learning

  Correct Answer: A

  References: https://www.linkedin.com/pulse/getting-started-azure-iot-services-stream-analytics-rob-tiffany

• Question 23:

  Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while

  others might not have a correct solution.

  After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

  You have Azure IoT Edge devices that generate streaming data.

  On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.

  Solution: You deploy Azure Functions as an IoT Edge module.

  Does this meet the goal?

  A. Yes

  B. No

  Correct Answer: B

  Instead use Azure Stream Analytics and REST API.

  Note. Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies: temporary and

  persistent.

  Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints.

  References:

  https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection

• Question 24:

  Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while

  others might not have a correct solution.

  After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

  You have Azure IoT Edge devices that generate streaming data.

  On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.

  Solution: You deploy Azure Stream Analytics as an IoT Edge module.

  Does this meet the goal?

  A. Yes

  B. No

  Correct Answer: A

  Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies: temporary and persistent.

  Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints.

  References:

  https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection

• Question 25:

  You are designing an AI solution that will analyze millions of pictures by using Azure HDInsight Hadoop cluster.

  You need to recommend a solution for storing the pictures. The solution must minimize costs.

  Which storage solution should you recommend?

  A. an Azure Data Lake Storage Gen1

  B. Azure File Storage

  C. Azure Blob storage

  D. Azure Table storage

  Correct Answer: C

  Data Lake will be a bit more expensive although they are in close range of each other. Blob storage has more options for pricing depending upon things like how frequently you need to access your data (cold vs hot storage).

  References: http://blog.pragmaticworks.com/azure-data-lake-vs-azure-blob-storage-in-data-warehousing

• Question 26:

  You are configuring data persistence for a Microsoft Bot Framework application. The application requires a structured NoSQL cloud data store.

  You need to identify a storage solution for the application. The solution must minimize costs.

  What should you identify?

  A. Azure Blob storage

  B. Azure Cosmos DB

  C. Azure HDInsight

  D. Azure Table storage

  Correct Answer: D

  Table Storage is a NoSQL key-value store for rapid development using massive semi-structured datasets You can develop applications on Cosmos DB using popular NoSQL APIs.

  Both services have a different scenario and pricing model.

  While Azure Storage Tables is aimed at high capacity on a single region (optional secondary read only region but no failover), indexing by PK/RK and storage-optimized pricing; Azure Cosmos DB Tables aims for high throughput (single-digit millisecond latency), global distribution (multiple failover), SLA-backed predictive performance with automatic indexing of each attribute/property and a pricing model focused on throughput.

  References: https://db-engines.com/en/system/Microsoft+Azure+Cosmos+DB%3BMicrosoft+Azure+Table+Storage

• Question 27:

  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.

  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

  Correct Answer: BDE

  The process of securing a new web service or an existing one is as follows:

  1.

  Get a domain name.

  2.

  Get a digital certificate.

  3.

  Deploy or update the web service with the SSL setting enabled.

  4.

  Update your DNS to point to the web service.

  Note: To deploy (or re-deploy) the service with SSL enabled, set the ssl_enabled parameter to True, wherever applicable. Set the ssl_certificate parameter to the value of the certificate file and the ssl_key to the value of the key file.

  References:

  https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-secure-web-service

• Question 28:

  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?

  A. Azure Queue storage

  B. Azure Cosmos DB

  C. Azure Blob storage

  D. Azure SQL Database

  Correct Answer: C

  References: https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage

• Question 29:

  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.

  A. Microsoft Visual Studio Code

  B. Azure Notebooks

  C. Azure Machine Learning Studio

  D. Microsoft Visual Studio

  Correct Answer: C

  References: https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/machine-learning/studio/algorithm-choice.md

• Question 30:

  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?

  A. horizontal pod autoscaler

  B. cluster autoscaler

  C. manual scaling

  D. Azure Container Instances

  Correct Answer: B

  To keep up with application demands in Azure Kubernetes Service (AKS), you may need to adjust the number of nodes that run your workloads. The cluster autoscaler component can watch for pods in your cluster that can't be scheduled because of resource constraints. When issues are detected, the number of nodes is increased to meet the application demand. Nodes are also regularly checked for a lack of running pods, with the number of nodes then decreased as needed. This ability to automatically scale up or down the number of nodes in your AKS cluster lets you run an efficient, cost-effective cluster.

  References: https://docs.microsoft.com/en-us/azure/aks/cluster-autoscaler