Microsoft Microsoft Certifications AI-100 Questions & Answers

• Question 81:

  You plan to perform analytics of the medical records of patients located around the world. You need to recommend a solution that avoids storing and processing data in the cloud. What should you include in the recommendation?

  A. Azure Machine Learning Studio

  B. the Text Analytics API that has container support

  C. Azure Machine Learning services

  D. an Apache Spark cluster that uses MMLSpark

  Correct Answer: D

  The Microsoft Machine Learning Library for Apache Spark (MMLSpark) assists in provisioning scalable machine learning models for large datasets, especially for building deep learning problems. MMLSpark works with SparkML pipelines, including Microsoft CNTK and the OpenCV library, which provide end-to-end support for the ingress and processing of image input data, categorization of images, and text analytics using pre-trained deep learning algorithms.

  References: https://subscription.packtpub.com/book/big_data_and_business_intelligence/9781789131956/10/ch10lvl1sec61/an-overview-of-the-microsoft-machine-learning-library-for-apache-spark-mmlspark

• Question 82:

  Your company has an on-premises datacenter.

  You plan to publish an app that will recognize a set of individuals by using the Face API. The model is trained.

  You need to ensure that all images are processsed in the on-premises datacenter.

  What should you deploy to host the Face API?

  A. a Docker container

  B. Azure File Sync

  C. Azure Application Gateway

  D. Azure Data Box Edge

  Correct Answer: A

  A container is a standard unit of software that packages up code and all its dependencies so the application runs quickly and reliably from one computing environment to another. A Docker container image is a lightweight, standalone, executable package of software that includes everything needed to run an application: code, runtime, system tools, system libraries and settings.

  Incorrect Answers:

  D: Azure Data Box Edge is an AI-enabled edge computing device with network data transfer capabilities. This article provides you an overview of the Data Box Edge solution, benefits, key capabilities, and the scenarios where you can deploy this device.

  Data Box Edge is a Hardware-as-a-service solution. Microsoft ships you a cloud-managed device with a built-in Field Programmable Gate Array (FPGA) that enables accelerated AI-inferencing and has all the capabilities of a storage gateway.

  References: https://www.docker.com/resources/what-container

• Question 83:

  You have a Bing Search service that is used to query a product catalog. You need to identify the following information:

  1.

  The locale of the query

  2.

  The top 50 query strings

  3.

  The number of calls to the service

  4.

  The top geographical regions of the service What should you implement?

  A. Bing Statistics

  B. Azure API Management (APIM)

  C. Azure Monitor

  D. Azure Application Insights

  Correct Answer: A

  The Bing Statistics add-in provides metrics such as call volume, top queries, API response, code distribution, and market distribution. The rich slicing-and-dicing capability lets you gather deeper understanding of your users and their usage to inform your business strategy.

  References: https://www.bingapistatistics.com/

• Question 84:

  You have a Face API solution that updates in real time. A pilot of the solution runs successfully on a small dataset.

  When you attempt to use the solution on a larger dataset that continually changes, the performance degrades, slowing how long it takes to recognize existing faces.

  You need to recommend changes to reduce the time it takes to recognize existing faces without increasing costs.

  What should you recommend?

  A. Change the solution to use the Computer Vision API instead of the Face API.

  B. Separate training into an independent pipeline and schedule the pipeline to run daily.

  C. Change the solution to use the Bing Image Search API instead of the Face API.

  D. Distribute the face recognition inference process across many Azure Cognitive Services instances.

  Correct Answer: B

  Incorrect Answers:

  A: The purpose of Computer Vision is to inspects each image associated with an incoming article to (1) scrape out written words from the image and (2) determine what types of objects are present in the image.

  C: The Bing API provides an experience similar to Bing.com/search by returning search results that Bing determines are relevant to a user's query. The results include Web pages and may also include images, videos, and more.

  D: That would increase cost.

  References: https://github.com/Azure/cognitive-services

• Question 85:

  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. Azure Table storage

  B. Azure File Storage

  C. Azure Data Lake Storage Gen2

  D. Azure Data Lake Storage Gen1

  Correct Answer: D

  Azure Data Lake Storage Gen1 is adequate and less expensive compared to Gen2.

  References: https://visualbi.com/blogs/microsoft/introduction-azure-data-lake-gen2/

• Question 86:

  You deploy an application that performs sentiment analysis on the data stored in Azure Cosmos DB.

  Recently, you loaded a large amount of data to the database. The data was for a customer named Contoso, Ltd.

  You discover that queries for the Contoso data are slow to complete, and the queries slow the entire application.

  You need to reduce the amount of time it takes for the queries to complete. The solution must minimize costs.

  What should you do? More than one answer choice may achieve the goal. (Choose two.)

  A. Change the request units.

  B. Change the partitioning strategy.

  C. Change the transaction isolation level.

  D. Migrate the data to the Cosmos DB database.

  Correct Answer: AB

  Increasing request units would improve throughput, but at a cost.

  Throughput provisioned for a container is divided evenly among physical partitions.

  References:

  https://docs.microsoft.com/en-us/azure/architecture/best-practices/data-partitioning

• Question 87:

  Your company has several AI solutions and bots.

  You need to implement a solution to monitor the utilization of the bots. The solution must ensure that analysts at the company can generate dashboards to review the utilization.

  What should you include in the solution?

  A. Azure Application Insights

  B. Azure Data Explorer

  C. Azure Logic Apps

  D. Azure Monitor

  Correct Answer: A

  Bot Analytics.

  Analytics is an extension of Application Insights. Application Insights provides service-level and instrumentation data like traffic, latency, and integrations. Analytics provides conversation-level reporting on user, message, and channel data.

  References:

  https://docs.microsoft.com/en-us/azure/bot-service/bot-service-manage-analytics

• Question 88:

  Your plan to design a bot that will be hosted by using Azure Bot Service. Your company identifies the following compliance requirements for the bot:

  1.

  Payment Card Industry Data Security Standards (PCI DSS)

  2.

  General Data Protection Regulation (GDPR)

  3.

  ISO 27001

  You need to identify which compliance requirements are met by hosting the bot in the bot service.

  What should you identify?

  A. PCI DSS only

  B. PCI DSS, ISO 27001, and GDPR

  C. ISO 27001 only

  D. GDPR only

  Correct Answer: B

  Azure Bot service is compliant with ISO 27001:2013, ISO 27019:2014, SOC 1 and 2, Payment Card Industry Data Security Standard (PCI DSS), and Health Insurance Portability and Accountability Act Business Associate Agreement (HIPAA BAA).

  Microsoft products and services, including Azure Bot Service, are available today to help you meet the GDPR requirements.

  References:

  https://docs.microsoft.com/en-us/azure/bot-service/bot-service-compliance

  https://blog.botframework.com/2018/04/23/general-data-protection-regulation-gdpr/

• Question 89:

  Your company plans to create a mobile app that will be used by employees to query the employee handbook.

  You need to ensure that the employees can query the handbook by typing or by using speech.

  Which core component should you use for the app?

  A. Language Understanding (LUIS)

  B. QnA Maker

  C. Text Analytics

  D. Azure Search

  Correct Answer: A

  "Together, Language Understanding and Azure Bot Service enable developers to create conversational interfaces for various scenarios like banking, travel, and entertainment. For example, a hotel's concierge can use a bot to enhance traditional e-mail and phone call interactions by validating a customer via Azure Active Directory and using Cognitive Services to better contextually process customer requests using text and voice. The Speech recognition service can be added to support voice commands"

• Question 90:

  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 need to create an IoT solution that performs the following tasks:

  1.

  Identifies hazards

  2.

  Provides a real-time online dashboard

  3.

  Takes images of an area every minute

  4.

  Counts the number of people in an area every minute

  Solution: You implement Azure Cognitive Services containers on the IoT devices, and then you configure results to be sent to an Azure IoT hub. You configure Microsoft Power BI to connect to the IoT hub by using Azure Stream Analytics.

  Does this meet the goal?

  A. Yes

  B. No

  Correct Answer: A

  There is support for running Azure Cognitive Services containers for Text Analytics and Language Understanding containers on edge devices with Azure IoT Edge. This means that all your workloads can be run locally where your data is

  being generated while keeping the simplicity of the cloud to manage them remotely, securely and at scale.

  You would have to set up an IoT Edge device and its IoT Hub.

  Note: Azure Stream Analytics enables you to take advantage of one of the leading business intelligence tools, Microsoft Power BI.

  Get your IoT hub ready for data access by adding a consumer group.

  Create, configure, and run a Stream Analytics job for data transfer from your IoT hub to your Power BI account.

  Create and publish a Power BI report to visualize the data.

  References:

  https://azure.microsoft.com/es-es/blog/running-cognitive-services-on-iot-edge/

  https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-live-data-visualization-in-power-bi