Download Microsoft.AI-100.Train4Sure.2019-04-03.23q.vcex

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Exam Designing and Implementing an Azure AI Solution
Number AI-100
File Name Microsoft.AI-100.Train4Sure.2019-04-03.23q.vcex
Size 116 KB
Posted Apr 03, 2019
Download Microsoft.AI-100.Train4Sure.2019-04-03.23q.vcex

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Demo Questions

Question 1

You are designing an AI solution that will analyze millions of pictures. 
You need to recommend a solution for storing the pictures. The solution must minimize costs. 
Which storage solution should you recommend?


  1. an Azure Data Lake store
  2. Azure File Storage
  3. Azure Blob storage
  4. Azure Table storage
Correct answer: C
Explanation:
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
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 2

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.


  1. Generate a shared access signature (SAS)
  2. Obtain an SSL certificate
  3. Add a deployment slot
  4. Update the web service
  5. Update DNS
  6. Create an Azure Key Vault
Correct answer: BDE
Explanation:
The process of securing a new web service or an existing one is as follows:Get a domain name. Get a digital certificate. Deploy or update the web service with the SSL setting enabled. 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
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 3

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?


  1. Azure Queue storage
  2. Azure Cosmos DB
  3. Azure Blob storage
  4. Azure SQL Database
Correct answer: C
Explanation:
References:https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/data-storage



Question 4

Your company has 1,000 AI developers who are responsible for provisioning environments in Azure. 
You need to control the type, size, and location of the resources that the developers can provision. 
What should you use?


  1. Azure Key Vault
  2. Azure service principals
  3. Azure managed identities
  4. Azure Security Center
  5. Azure Policy
Correct answer: B
Explanation:
When an application needs access to deploy or configure resources through Azure Resource Manager in Azure Stack, you create a service principal, which is a credential for your application. You can then delegate only the necessary permissions to that service principal. References:https://docs.microsoft.com/en-us/azure/azure-stack/azure-stack-create-service-principals
When an application needs access to deploy or configure resources through Azure Resource Manager in Azure Stack, you create a service principal, which is a credential for your application. You can then delegate only the necessary permissions to that service principal. 
References:
https://docs.microsoft.com/en-us/azure/azure-stack/azure-stack-create-service-principals



Question 5

You are designing an AI solution in Azure that will perform image classification. 
You need to identify which processing platform will provide you with the ability to update the logic over time. The solution must have the lowest latency for inferencing without having to batch. 
Which compute target should you identify?


  1. graphics processing units (GPUs)
  2. field-programmable gate arrays (FPGAs)
  3. central processing units (CPUs)
  4. application-specific integrated circuits (ASICs)
Correct answer: B
Explanation:
FPGAs, such as those available on Azure, provide performance close to ASICs. They are also flexible and reconfigurable over time, to implement new logic. Incorrect Answers:D: ASICs are custom circuits, such as Google's TensorFlow Processor Units (TPU), provide the highest efficiency. They can't be reconfigured as your needs change.References:https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-accelerate-with-fpgas
FPGAs, such as those available on Azure, provide performance close to ASICs. They are also flexible and reconfigurable over time, to implement new logic. 
Incorrect Answers:
D: ASICs are custom circuits, such as Google's TensorFlow Processor Units (TPU), provide the highest efficiency. They can't be reconfigured as your needs change.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/concept-accelerate-with-fpgas



Question 6

Your company has recently deployed 5,000 Internet-connected sensors for a planned AI solution. 
You need to recommend a computing solution to perform a real-time analysis of the data generated by the sensors. 
Which computing solution should you recommend?


  1. an Azure HDInsight Storm cluster
  2. Azure Notification Hubs
  3. an Azure HDInsight Hadoop cluster
  4. an Azure HDInsight R cluster
Correct answer: C
Explanation:
Azure HDInsight makes it easy, fast, and cost-effective to process massive amounts of data. You can use HDInsight to process streaming data that's received in real time from a variety of devices. References:https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-introduction
Azure HDInsight makes it easy, fast, and cost-effective to process massive amounts of data. 
You can use HDInsight to process streaming data that's received in real time from a variety of devices. 
References:
https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-introduction



Question 7

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 are developing an application that uses an Azure Kubernetes Service (AKS) cluster. 
You are troubleshooting a node issue. 
You need to connect to an AKS node by using SSH. 
Solution: You change the permissions of the AKS resource group, and then you create an SSH connection.
Does this meet the goal?


  1. Yes
  2. No
Correct answer: B
Explanation:
Instead add an SSH key to the node, and then you create an SSH connection. References:https://docs.microsoft.com/en-us/azure/aks/ssh
Instead add an SSH key to the node, and then you create an SSH connection. 
References:
https://docs.microsoft.com/en-us/azure/aks/ssh



Question 8

You are developing a Computer Vision application. 
You plan to use a workflow that will load data from an on-premises database to Azure Blob storage, and then connect to an Azure Machine Learning service. 
What should you use to orchestrate the workflow?


  1. Azure Kubernetes Service (AKS)
  2. Azure Pipelines
  3. Azure Data Factory
  4. Azure Container Instances
Correct answer: C
Explanation:
With Azure Data Factory you can use workflows to orchestrate data integration and data transformation processes at scale. Build data integration, and easily transform and integrate big data processing and machine learning with the visual interface. References:https://azure.microsoft.com/en-us/services/data-factory/
With Azure Data Factory you can use workflows to orchestrate data integration and data transformation processes at scale. 
Build data integration, and easily transform and integrate big data processing and machine learning with the visual interface. 
References:
https://azure.microsoft.com/en-us/services/data-factory/



Question 9

You plan to design a solution for an AI implementation that uses data from IoT devices. 
You need to recommend a data storage solution for the IoT devices that meets the following requirements:
  • Allow data to be queried in real-time as it streams into the solution. 
  • Provide the lowest amount of latency for loading data into the solution. 
What should you include in the recommendation?


  1. a Microsoft Azure Table Storage solution
  2. a Microsoft Azure HDInsight R Server cluster
  3. a Microsoft Azure HDInsight Hadoop cluster
  4. a Microsoft Azure SQL database that has In-Memory OLTP enabled
Correct answer: C
Explanation:
You can use HDInsight to process streaming data that's received in real time from a variety of devices. Internet of Things (IoT) You can use HDInsight to build applications that extract critical insights from data. You can also use Azure Machine Learning on top of that to predict future trends for your business. By combining enterprise-scale R analytics software with the power of Apache Hadoop and Apache Spark, Microsoft R Server for HDInsight gives you the scale and performance you need. Multi-threaded math libraries and transparent parallelization in R Server handle up to 1000x more data and up to 50x faster speeds than open-source R, which helps you to train more accurate models for better predictions. References:https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-introduction
You can use HDInsight to process streaming data that's received in real time from a variety of devices. 
Internet of Things (IoT) 
You can use HDInsight to build applications that extract critical insights from data. You can also use Azure Machine Learning on top of that to predict future trends for your business. 
By combining enterprise-scale R analytics software with the power of Apache Hadoop and Apache Spark, Microsoft R Server for HDInsight gives you the scale and performance you need. Multi-threaded math libraries and transparent parallelization in R Server handle up to 1000x more data and up to 50x faster speeds than open-source R, which helps you to train more accurate models for better predictions. 
References:
https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-introduction



Question 10

You are designing an AI workflow that will aggregate data stored in Azure as JSON documents. 
You expect to store more than 2 TB of new data daily. 
You need to choose the data storage service for the data. The solution must minimize costs. 
Which data storage service should you choose?


  1. Azure Manage Disks
  2. Azure Blob Storage
  3. Azure File Storage
  4. Azure Data Lake Storage
Correct answer: B
Explanation:
Generally, 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). Data Lake is priced on volume, so it will go up as you reach certain tiers of volume. References:http://blog.pragmaticworks.com/azure-data-lake-vs-azure-blob-storage-in-data-warehousing
Generally, 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). Data Lake is priced on volume, so it will go up as you reach certain tiers of volume. 
References:
http://blog.pragmaticworks.com/azure-data-lake-vs-azure-blob-storage-in-data-warehousing









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