Practice Free AI-102 Exam Online Questions
HOTSPOT
You have an Azure subscription that contains an Azure OpenA1 resource named All.
You plan to develop a console app that will answer user questions.
You need to call All and output the results to the console.
How should you complete the code? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.
You plan to perform predictive maintenance.
You collect IoT sensor data from 100 industrial machines for a year. Each machine has 50 different sensors that generate data at one-minute intervals. In total, you have 5,000 time series datasets.
You need to identify unusual values in each time series to help predict machinery failures.
Which Azure Cognitive Services service should you use?
- A . Anomaly Detector
- B . Cognitive Search
- C . Form Recognizer
- D . Custom Vision
Which database transaction property ensures that individual transactions are executed only once and either succeed in their entirety or roll back?
- A . consistency
- B . isolation
- C . atomicity
- D . durability
HOTSPOT
You are developing the knowledgebase by using Azure Cognitive Search.
You need to build a skill that will be used by indexers.
How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Explanation:
Box 1: "categories": ["Locations", "Persons", "Organizations"], Locations, Persons, Organizations are in the outputs.
Scenario: Contoso plans to develop a searchable knowledgebase of all the intellectual property
Note: The categories parameter is an array of categories that should be extracted. Possible category types: "Person", "Location", "Organization", "Quantity", "Datetime", "URL", "Email". If no category is provided, all types are returned.
Box 2: {"name": " entities"}
The include wikis, so should include entities in the outputs.
Note: entities is an array of complex types that contains rich information about the entities extracted from text, with the following fields
name (the actual entity name. This represents a "normalized" form)
wikipediaId
wikipediaLanguage
wikipediaUrl (a link to Wikipedia page for the entity)
etc.
Reference: https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition
DRAG DROP
You plan to build a chatbot to support task tracking.
You create a Conversational Language Understanding service named Iu1.
You need to build a Conversational Language Understanding model to Integrate into the chatbot. The solution must minimize development time to build the model.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Topic 2, Contoso, Ltd.
Case Study
This is a case study Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab. note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
General Overview
Contoso, Ltd. is an international accounting company that has offices in France. Portugal, and the United Kingdom.
Contoso has a professional services department that contains the roles shown in the following table.
Infrastructure
Contoso has the following subscriptions:
• Azure
• Microsoft 365
• Microsoft Dynamics 365
Azure Active (Azure AD) Directory
Contoso has Azure Active Directory groups for securing role-based access.
The company uses the following group naming conventions:
• ICountryJ-[Levell-[Role]
• [Level]-[Role]
Intellectual Property
Contoso has the intellectual property shown in the following table.
Text-based content is provided only in one language and is not translated.
Planned Projects
Contoso plans to develop the following:
• A document processing workflow to extract information automatically from PDFs and images of financial documents
• A customer-support chatbot that will answer questions by using FAQs
• A searchable knowledgebase of all the intellectual property
Technical Requirements
Contoso identifies the following technical requirements:
• All content must be approved before being published.
• All planned projects must support English, French, and Portuguese.
• All content must be secured by using role-based access control (RBAC).
• RBAC role assignments must use the principle of least privilege.
• RBAC roles must be assigned only to Azure Active Directory groups.
• Al solution responses must have a confidence score that is equal to or greater than 70 percent.
• When the response confidence score of an Al response is lower than 70 percent, the response must be improved by human input.
Chatbot Requirements
Contoso identifies the following requirements for the chatbot:
• Provide customers with answers to the FAQs.
• Ensure that the customers can chat to a customer service agent.
• Ensure that the members of a group named Management-Accountants can approve the FAQs.
• Ensure that the members of a group named Consultant-Accountants can create and amend the FAQs.
• Ensure that the members of a group named the Agent-CustomerServices can browse the FAQs.
• Ensure that access to the customer service agents is managed by using Omnichannel for Customer Service.
• When the response confidence score is low. ensure that the chatbot can provide other response options to the customers.
Document Processing Requirements
Contoso identifies the following requirements for document processing:
• The document processing solution must be able to process standardized financial documents that have the following characteristics:
• Contain fewer than 20 pages.
• Be formatted as PDF or JPEG files.
• Have a distinct standard for each office.
• The document processing solution must be able to extract tables and text from the financial documents.
• The document processing solution must be able to extract information from receipt images.
• Members of a group named Management-Bookkeeper must define how to extract tables from the financial documents.
• Members of a group named Consultant-Bookkeeper must be able to process the financial documents.
Knowledgebase Requirements
Contoso identifies the following requirements for the knowledgebase:
• Supports searches for equivalent terms
• Can transcribe jargon with high accuracy
• Can search content in different formats, including video
• Provides relevant links to external resources for further research
You need to develop an extract solution for the receipt images. The solution must meet the document processing requirements and the technical requirements.
You upload the receipt images to the From Recognizer API for analysis, and the API returns the following JSON.
Which expression should you use to trigger a manual review of the extracted information by a member of the Consultant-Bookkeeper group?
- A . documentResults.docType == "prebuilt:receipt"
- B . documentResults.fields.".confidence < 0.7
- C . documentResults.fields.ReceiptType.confidence > 0.7
- D . documentResults.fields.MerchantName.confidence < 0.7
D
Explanation:
Need to specify the field name, and then use < 0.7 to handle trigger if confidence score is less than 70%.
Reference: https://docs.microsoft.com/en-us/azure/applied-ai-services/form-recognizer/api-v2-0/reference-sdk-api-v2-0
You have the following C# function.
You call the function by using the following code.
Following ‘key phrases’ what output will you receive?
- A . Jumps over the
- B . The quick brown fox jumps over the lazy dog
- C . Quick brown fox lazy dog
- D . The quick
DRAG DROP
You are building a Language Understanding model for purchasing tickets.
You have the following utterance for an intent named PurchaseAndSendTickets.
Purchase [2 audit business] tickets to [Paris] [next Monday] and send tickets to [[email protected]]
You need to select the entity types. The solution must use built-in entity types to minimize training data whenever possible.
Which entity type should you use for each label? To answer, drag the appropriate entity types to the correct labels. Each entity type 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.
Explanation:
Box 1: GeographyV2
The prebuilt geographyV2 entity detects places. Because this entity is already trained, you do not need to add example utterances containing GeographyV2 to the application intents.
Box 2: Email
Email prebuilt entity for a LUIS app: Email extraction includes the entire email address from an utterance. Because this entity is already trained, you do not need to add example utterances containing email to the application intents.
Box 3: Machine learned
The machine-learning entity is the preferred entity for building LUIS applications.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-geographyv2
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-reference-prebuilt-email
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/reference-entity-machine-learned-entity
You manage an application that stores data in a shared folder on a Windows server. You need to move the shared folder to Azure Storage.
Which type of Azure Storage should you use?
- A . table
- B . queue
- C . file
- D . blob
You have an app named App1 that uses a custom Azure Al Document Intelligence model to recognize contract documents. You need to ensure that the model supports an additional contract format. The solution must minimize development effort.
What should you do?
- A . Lower the confidence score threshold of App1.
- B . Lower the accuracy threshold of App1.
- C . Add the additional contract format to the existing training set. Retrain the model.
- D . Create a new training set and add the additional contract format to the new training set.
- E . Create and train a new custom model.