Practical Microsoft AI-100 Preparation Exams Online

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Free demo questions for Microsoft AI-100 Exam Dumps Below:

NEW QUESTION 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.

  • A. SQL
  • B. Spark
  • C. local parallel
  • D. HBase
  • E. local sequential

Answer: ABC

Explanation:
Remote computing is available for specific data sources on selected platforms. The following tables document the supported combinations.
RxInSqlServer, sqlserver: Remote compute context. Target server is a single database node (SQL Server 2016 R Services or SQL Server 2017 Machine Learning Services). Computation is parallel, but not distributed.
RxSpark, spark: Remote compute context. Target is a Spark cluster on Hadoop.
RxLocalParallel, localpar: Compute context is often used to enable controlled, distributed computations relying on instructions you provide rather than a built-in scheduler on Hadoop. You can use compute context for manual distributed computing.
References:
https://docs.microsoft.com/en-us/machine-learning-server/r/concept-what-is-compute-context

NEW QUESTION 2

You are designing an Al application that will perform real-time processing by using Microsoft Azure Stream Analytics.
You need to identify the valid outputs of a Stream Analytics job.
What are three possible outputs? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

  • A. a Hive table in Azure HDInsight
  • B. Azure SQL Database
  • C. Azure Cosmos DB
  • D. Azure Blob storage
  • E. Azure Redis Cache

Answer: BCD

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

NEW QUESTION 3

You deploy an Azure bot.
You need to collect Key Performance Indicator (KPI) data from the bot. The type of data includes:
• The number of users interacting with the bot
• The number of messages interacting with the bot
• The number of messages on different channels received by the bot
• The number of users and messages continuously interacting with the bot What should you configure?

  • A. Bot analytics
  • B. Azure Monitor
  • C. Azure Analysis Services
  • D. Azure Application Insights

Answer: A

Explanation:
References:
https://docs.microsoft.com/en-us/azure/sql-database/saas-multitenantdb-adhoc-reporting

NEW QUESTION 4

You are developing a mobile application that will perform optical character recognition (OCR) from photos. The application will annotate the photos by using metadata, store the photos in Azure Blob storage, and then score the photos by using an Azure Machine Learning model.
What should you use to process the data?

  • A. Azure Event Hubs
  • B. Azure Functions
  • C. Azure Stream Analytics
  • D. Azure Logic Apps

Answer: A

NEW QUESTION 5

You have thousands of images that contain text.
You need to process the text from the images into a machine-readable character stream. Which Azure Cognitive Services service should you use?

  • A. Translator Text
  • B. Text Analytics
  • C. Computer Vision
  • D. the Image Moderation API

Answer: C

Explanation:
With Computer Vision you can detect text in an image using optical character recognition (OCR) and extract the recognized words into a machine-readable character stream.
References:
https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/ https://docs.microsoft.com/en-us/azure/cognitive-services/content-moderator/image-moderation-api

NEW QUESTION 6

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

Answer: A

Explanation:
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

NEW QUESTION 7

You have a solution that runs on a five-node Azure Kubernetes Service (AKS) cluster. The cluster uses an Nseries virtual machine.
An Azure Batch AI process runs once a day and rarely on demand.
You need to recommend a solution to maintain the cluster configuration when the cluster is not in use. The solution must not incur any compute costs.
What should you include in the recommendation?

  • A. Downscale the cluster to one node
  • B. Downscale the cluster to zero nodes
  • C. Delete the cluster

Answer: A

Explanation:
An AKS cluster has one or more nodes. References:
https://docs.microsoft.com/en-us/azure/aks/concepts-clusters-workloads

NEW QUESTION 8

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 in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create several Al models in Azure Machine Learning Studio. You deploy the models to a production environment.
You need to monitor the compute performance of the models. Solution: You create environment files.
Does this meet the goal?

  • A. Yes
  • B. No

Answer: B

Explanation:
You need to enable Model data collection. References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-data-collection

NEW QUESTION 9

Your company has recently purchased and deployed 25,000 IoT devices.
You need to recommend a data analysis solution for the devices that meets the following requirements:
AI-100 dumps exhibit Each device must use its own credentials for identity.
AI-100 dumps exhibit Each device must be able to route data to multiple endpoints.
AI-100 dumps exhibit The solution must require the minimum amount of customized code. What should you include in the recommendation?

  • A. Microsoft Azure Notification Hubs
  • B. Microsoft Azure Event Hubs
  • C. Microsoft Azure IoT Hub
  • D. Microsoft Azure Service Bus

Answer: C

Explanation:
An IoT hub has a default built-in endpoint. You can create custom endpoints to route messages to by linking other services in your subscription to the hub.
Individual devices connect using credentials stored in the IoT hub's identity registry. References:
https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-devguide-security

NEW QUESTION 10

You create an Azure Cognitive Services resource.
A data scientist needs to call the resource from Azure Logic Apps.
Which two values should you provide to the data scientist? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

  • A. endpoint URL
  • B. resource name
  • C. access key
  • D. resource group name
  • E. subscription ID

Answer: DE

Explanation:
References:
https://social.technet.microsoft.com/wiki/contents/articles/36074.logic-apps-with-azure-cognitive-service.aspx

NEW QUESTION 11

You plan to deploy two AI applications named AI1 and AI2. The data for the applications will be stored in a relational database.
You need to ensure that the users of AI1 and AI2 can see only data in each user’s respective geographic
region. The solution must be enforced at the database level by using row-level security. Which database solution should you use to store the application data?

  • A. Microsoft SQL Server on a Microsoft Azure virtual machine
  • B. Microsoft Azure Database for MySQL
  • C. Microsoft Azure Data Lake Store
  • D. Microsoft Azure Cosmos DB

Answer: A

Explanation:
Row-level security is supported by SQL Server, Azure SQL Database, and Azure SQL Data Warehouse. References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/row-level-security?view=sql-server-2017

NEW QUESTION 12

You are designing a solution that will ingest data from an Azure loT Edge device, preprocess the data in Azure Machine Learning, and then move the data to Azure HDInsight for further processing.
What should you include in the solution? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
AI-100 dumps exhibit

  • A. Mastered
  • B. Not Mastered

Answer: A

Explanation:
Box 1: Export Data
The Export data to Hive option in the Export Data module in Azure Machine Learning Studio. This option is useful when you are working with very large datasets, and want to save your machine learning experiment data to a Hadoop cluster or HDInsight distributed storage.
Box 2: Apache Hive
Apache Hive is a data warehouse system for Apache Hadoop. Hive enables data summarization, querying, and analysis of data. Hive queries are written in HiveQL, which is a query language similar to SQL.
Box 3: Azure Data Lake
Default storage for the HDFS file system of HDInsight clusters can be associated with either an Azure Storage account or an Azure Data Lake Storage.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/export-to-hive-query https://docs.microsoft.com/en-us/azure/hdinsight/hadoop/hdinsight-use-hive

NEW QUESTION 13

You plan to use the Microsoft 8ot Framework to develop bots that will be deployed by using the Azure Bot Service.
You need to configure the Azure Bot Service to support the following types of bots:
•Bots that use Azure Functions
•Bots that set a timer
Which template should you use for each bot type? To answer, drag the appropriate templates to the correct bot types. Each template may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
AI-100 dumps exhibit

  • A. Mastered
  • B. Not Mastered

Answer: A

Explanation:
References:
https://docs.microsoft.com/en-us/azure/bot-service/bot-service-concept-templates?view=azure-bot-service-3.0

NEW QUESTION 14

You develop a custom application that uses a token to connect to Azure Cognitive Services resources. A new security policy requires that all access keys are changed every 30 days.
You need to recommend a solution to implement the security policy.
Which three actions should you recommend be performed every 30 days? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
AI-100 dumps exhibit

  • A. Mastered
  • B. Not Mastered

Answer: A

Explanation:
Step 1: Generate new keys in the Cognitive Service resources
AI-100 dumps exhibit
Step 2: Retrieve a token from the Cognitive Services endpoint Step 3: Update the custom application to use the new authorization
Each request to an Azure Cognitive Service must include an authentication header. This header passes along a subscription key or access token, which is used to validate your subscription for a service or group of services.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/authentication

NEW QUESTION 15

You are designing a solution that will ingest temperature data from loT devices, calculate the average temperature, and then take action based on the aggregated data. The solution must meet the following requirements:
•Minimize the amount of uploaded data.
• Take action based on the aggregated data as quickly as possible.
What should you include in the solution? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
AI-100 dumps exhibit

  • A. Mastered
  • B. Not Mastered

Answer: A

Explanation:
Box 1: Azure Functions
Azure Function is a (serverless) service to host functions (little piece of code) that can be used for e. g. event driven applications.
General rule is always difficult since everything depends on your requirement but if you have to analyze a data stream, you should take a look at Azure Stream Analytics and if you want to implement something like a serverless event driven or timer-based application, you should check Azure Function or Logic Apps.
Note: Azure IoT Edge allows you to deploy complex event processing, machine learning, image recognition, and other high value AI without writing it in-house. Azure services like Azure Functions, Azure Stream Analytics, and Azure Machine Learning can all be run on-premises via Azure IoT Edge.
Box 2: An Azure IoT Edge device
Azure IoT Edge moves cloud analytics and custom business logic to devices so that your organization can focus on business insights instead of data management.
References:
https://docs.microsoft.com/en-us/azure/iot-edge/about-iot-edge

NEW QUESTION 16

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

Answer: C

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

NEW QUESTION 17

You are designing an AI solution that will provide feedback to teachers who train students over the Internet. The students will be in classrooms located in remote areas. The solution will capture video and audio data of the students in the classrooms.
You need to recommend Azure Cognitive Services for the AI solution to meet the following requirements: Alert teachers if a student seems angry or distracted.
Identify each student in the classrooms for attendance purposes.
Allow the teachers to log the text of conversations between themselves and the students. Which Cognitive Services should you recommend?

  • A. Computer Vision, Text Analytics, and Face API
  • B. Video Indexer, Face API, and Text Analytics
  • C. Computer Vision, Speech to Text, and Text Analytics
  • D. Text Analytics, QnA Maker, and Computer Vision
  • E. Video Indexer, Speech to Text, and Face API

Answer: E

Explanation:
Azure Video Indexer is a cloud application built on Azure Media Analytics, Azure Search, Cognitive Services (such as the Face API, Microsoft Translator, the Computer Vision API, and Custom Speech Service). It enables you to extract the insights from your videos using Video Indexer video and audio models.
Face API enables you to search, identify, and match faces in your private repository of up to 1 million people. The Face API now integrates emotion recognition, returning the confidence across a set of emotions for each face in the image such as anger, contempt, disgust, fear, happiness, neutral, sadness, and surprise. These emotions are understood to be cross-culturally and universally communicated with particular facial expressions.
Speech-to-text from Azure Speech Services, also known as speech-to-text, enables real-time transcription of audio streams into text that your applications, tools, or devices can consume, display, and take action on as command input. This service is powered by the same recognition technology that Microsoft uses for Cortana and Office products, and works seamlessly with the translation and text-to-speech.

NEW QUESTION 18

You plan to implement a new data warehouse for a planned AI solution. You have the following information regarding the data warehouse:
•The data files will be available in one week.
•Most queries that will be executed against the data warehouse will be ad-hoc queries.
•The schemas of data files that will be loaded to the data warehouse will change often.
•One month after the planned implementation, the data warehouse will contain 15 TB of data. You need to recommend a database solution to support the planned implementation.
What two solutions should you include in the recommendation? Each correct answer is a complete solution. NOTE: Each correct selection is worth one point.

  • A. Apache Hadoop
  • B. Apache Spark
  • C. a Microsoft Azure SQL database
  • D. an Azure virtual machine that runs Microsoft SQL Server

Answer: AB

NEW QUESTION 19

You need to recommend a data storage solution that meets the technical requirements.
What is the best data storage solution to recommend? More than one answer choice may achieve the goal. Select the BEST answer.

  • A. Azure Databricks
  • B. Azure SQL Database
  • C. Azure Table storage
  • D. Azure Cosmos DB

Answer: B

Explanation:
References:
https://docs.microsoft.com/en-us/azure/architecture/example-scenario/ai/commerce-chatbot

NEW QUESTION 20

You are designing an Al solution that must meet the following processing requirements:
• Use a parallel processing framework that supports the in-memory processing of high volumes of data.
• Use in-memory caching and a columnar storage engine for Apache Hive queries.
What should you use to meet each requirement? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
AI-100 dumps exhibit

  • A. Mastered
  • B. Not Mastered

Answer: A

Explanation:
Box 1: Apache Spark
Apache Spark is a parallel processing framework that supports in-memory processing to boost the performance of big-data analytic applications. Apache Spark in Azure HDInsight is the Microsoft implementation of Apache Spark in the cloud.
Box 2: Interactive Query
Interactive Query provides In-memory caching and improved columnar storage engine for Hive queries. References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-overview https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/interactive-query/apache-interactive-query-get-started

NEW QUESTION 21

You need to design an application that will analyze real-time data from financial feeds.
The data will be ingested into Azure IoT Hub. The data must be processed as quickly as possible in the order in which it is ingested.
Which service should you include in the design?

  • A. Azure Data Factory
  • B. Azure Queue storage
  • C. Azure Stream Analytics
  • D. Azure Notification Hubs

Answer: C

Explanation:
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/real-time-processing

NEW QUESTION 22

You need to build an API pipeline that analyzes streaming data. The pipeline will perform the following:
AI-100 dumps exhibit Visual text recognition
AI-100 dumps exhibit Audio transcription
AI-100 dumps exhibit Sentiment analysis
AI-100 dumps exhibit Face detection
Which Azure Cognitive Services should you use in the pipeline?

  • A. Custom Speech Service
  • B. Face API
  • C. Text Analytics
  • D. Video Indexer

Answer: D

Explanation:
Azure Video Indexer is a cloud application built on Azure Media Analytics, Azure Search, Cognitive Services (such as the Face API, Microsoft Translator, the Computer Vision API, and Custom Speech Service). It enables you to extract the insights from your videos using Video Indexer video and audio models described below:
Visual text recognition (OCR): Extracts text that is visually displayed in the video. Audio transcription: Converts speech to text in 12 languages and allows extensions.
Sentiment analysis: Identifies positive, negative, and neutral sentiments from speech and visual text. Face detection: Detects and groups faces appearing in the video.
References:
https://docs.microsoft.com/en-us/azure/media-services/video-indexer/video-indexer-overview

NEW QUESTION 23
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