Use Real AI-102 Dumps - Microsoft Correct Answers updated on 2021
Azure AI Engineer Associate AI-102 Exam Practice Dumps
Who should take the AI-102: Designing and Implementing an Azure AI Solution Exam
The AI-102 Exam certification is an internationally-recognized certification which help to have validation for Azure AI Solution Architects who have ability to accomplish the following technical tasks: analyze solution requirements; design solutions; integrate AI models into solutions; and deploy and manage solutions.
NEW QUESTION 41
You need to measure the public perception of your brand on social media messages. Which Azure Cognitive Services service should you use?
- A. Content Moderator
- B. Computer Vision
- C. Text Analytics
- D. Form Recognizer
Answer: C
Explanation:
Text Analytics Cognitive Service could be used to quickly determine the public perception for a specific topic, event or brand.
Example: A NodeJS app which pulls Tweets from Twitter using the Twitter API based on a specified search term. Then pass these onto Text Analytics for sentiment scoring before storing the data and building a visualisation in PowerBI. The Architecture looked something like this:
Reference:
https://www.linkedin.com/pulse/measuring-public-perception-azure-cognitive-services-steve-dalai
NEW QUESTION 42
You use the Custom Vision service to build a classifier.
After training is complete, you need to evaluate the classifier.
Which two metrics are available for review? Each correct answer presents a complete solution. (Choose two.) NOTE: Each correct selection is worth one point.
- A. weighted accuracy
- B. precision
- C. F-score
- D. area under the curve (AUC)
- E. recall
Answer: B,E
Explanation:
Explanation
Custom Vision provides three metrics regarding the performance of your model: precision, recall, and AP.
Reference:
https://www.tallan.com/blog/2020/05/19/azure-custom-vision/
NEW QUESTION 43
You are developing the smart e-commerce project.
You need to implement autocompletion as part of the Cognitive Search solution.
Which three actions should you perform? Each correct answer presents part of the solution. (Choose three.) NOTE: Each correct selection is worth one point.
- A. Set the analyzer property for the three product name variants.
- B. Add a suggester for each of the three product name fields.
- C. Set the searchAnalyzer property for the three product name variants.
- D. Make API queries to the search endpoint and include the product name fields in the searchFields query parameter.
- E. Use the default standard Lucene analyzer ("analyzer": null) or a language analyzer (for example, "analyzer": "en.Microsoft") on the field.
- F. Make API queries to the autocomplete endpoint and include suggesterName in the body.
- G. Add a suggester that has the three product name fields as source fields.
Answer: A,F,G
Explanation:
Scenario: Support autocompletion and autosuggestion based on all product name variants.
A: Call a suggester-enabled query, in the form of a Suggestion request or Autocomplete request, using an API. API usage is illustrated in the following call to the Autocomplete REST API.
POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2020-06-30
{
"search": "minecraf",
"suggesterName": "sg"
}
B: In Azure Cognitive Search, typeahead or "search-as-you-type" is enabled through a suggester. A suggester provides a list of fields that undergo additional tokenization, generating prefix sequences to support matches on partial terms. For example, a suggester that includes a City field with a value for "Seattle" will have prefix combinations of "sea", "seat", "seatt", and "seattl" to support typeahead.
Reference:
https://docs.microsoft.com/en-us/azure/search/index-add-suggesters
NEW QUESTION 44
You are building a chatbot by using the Microsoft Bot Framework SDK.
You use an object named UserProfile to store user profile information and an object named ConversationData to store information related to a conversation.
You create the following state accessors to store both objects in state.
var userStateAccessors = _userState.CreateProperty<UserProfile>(nameof(UserProfile)); var conversationStateAccessors = _conversationState.CreateProperty<ConversationData>(nameof(ConversationData)); The state storage mechanism is set to Memory Storage.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Yes
You create property accessors using the CreateProperty method that provides a handle to the BotState object. Each state property accessor allows you to get or set the value of the associated state property.
Box 2: Yes
Box 3: No
Before you exit the turn handler, you use the state management objects' SaveChangesAsync() method to write all state changes back to storage.
Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-howto-v4-state
NEW QUESTION 45
A customer uses Azure Cognitive Search.
The customer plans to enable a server-side encryption and use customer-managed keys (CMK) stored in Azure.
What are three implications of the planned change? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
- A. The index size will increase.
- B. Query times will decrease.
- C. Azure Key Vault is required.
- D. Query times will increase.
- E. The index size will decrease.
- F. A self-signed X.509 certificate is required.
Answer: A,B,D
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/search/search-security-overview
NEW QUESTION 46
You are planning the product creation project.
You need to recommend a process for analyzing videos.
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. (Choose four.)
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-us/blog/get-video-insights-in-even-more-languages/
https://docs.microsoft.com/en-us/azure/media-services/video-indexer/video-indexer-output-json-v2
NEW QUESTION 47
You are using a Language Understanding service to handle natural language input from the users of a web-based customer agent.
The users report that the agent frequently responds with the following generic response: "Sorry, I don't understand that." You need to improve the ability of the agent to respond to requests.
Which three 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. (Choose three.)
Answer:
Explanation:
Step 1: Add prebuilt domain models as required.
Prebuilt models provide domains, intents, utterances, and entities. You can start your app with a prebuilt model or add a relevant model to your app later.
Note: Language Understanding (LUIS) provides prebuilt domains, which are pre-trained models of intents and entities that work together for domains or common categories of client applications.
The prebuilt domains are trained and ready to add to your LUIS app. The intents and entities of a prebuilt domain are fully customizable once you've added them to your app.
Step 2: Enable active learning
To enable active learning, you must log user queries. This is accomplished by calling the endpoint query with the log=true querystring parameter and value.
Step 3: Train and republish the Language Understanding model
The process of reviewing endpoint utterances for correct predictions is called Active learning. Active learning captures endpoint queries and selects user's endpoint utterances that it is unsure of. You review these utterances to select the intent and mark entities for these real-world utterances. Accept these changes into your example utterances then train and publish. LUIS then identifies utterances more accurately.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-how-to-review-endpoint-utterances#log-user-
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-prebuilt-model
NEW QUESTION 48
You have 100 chatbots that each has its own Language Understanding model.
Frequently, you must add the same phrases to each model.
You need to programmatically update the Language Understanding models to include the new phrases.
How should you complete the code? To answer, drag the appropriate values to the correct targets. Each value 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.
Answer:
Explanation:
Box 1: AddPhraseListAsync
Example: Add phraselist feature
var phraselistId = await client.Features.AddPhraseListAsync(appId, versionId, new PhraselistCreateObject
{
EnabledForAllModels = false,
IsExchangeable = true,
Name = "QuantityPhraselist",
Phrases = "few,more,extra"
});
Box 2: PhraselistCreateObject
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/client-libraries-rest-api
NEW QUESTION 49
You build a custom Form Recognizer model.
You receive sample files to use for training the model as shown in the following table.
Which three files can you use to train the model? Each correct answer presents a complete solution. (Choose three.) NOTE: Each correct selection is worth one point.
- A. File6
- B. File3
- C. File1
- D. File5
- E. File2
- F. File4
Answer: A,B,C
Explanation:
Input requirements
Form Recognizer works on input documents that meet these requirements:
Format must be JPG, PNG, PDF (text or scanned), or TIFF. Text-embedded PDFs are best because there's no possibility of error in character extraction and location.
File size must be less than 50 MB.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/form-recognizer/overview
NEW QUESTION 50
You have the following data sources:
Finance: On-premises Microsoft SQL Server database
Sales: Azure Cosmos DB using the Core (SQL) API
Logs: Azure Table storage
HR: Azure SQL database
You need to ensure that you can search all the data by using the Azure Cognitive Search REST API. What should you do?
- A. Ingest the data in Logs into Azure Sentinel.
- B. Mirror Finance to an Azure SQL database.
- C. Configure multiple read replicas for the data in Sales.
- D. Migrate the data in Sales to the MongoDB API.
Answer: B
Explanation:
On-premises Microsoft SQL Server database cannot be used as an index data source.
Note: Indexer in Azure Cognitive Search: : Automate aspects of an indexing operation by configuring a data source and an indexer that you can schedule or run on demand. This feature is supported for a limited number of data source types on Azure.
Indexers crawl data stores on Azure.
Azure Blob Storage
Azure Data Lake Storage Gen2 (in preview)
Azure Table Storage
Azure Cosmos DB
Azure SQL Database
SQL Managed Instance
SQL Server on Azure Virtual Machines
Reference:
https://docs.microsoft.com/en-us/azure/search/search-indexer-overview#supported-data-sources
NEW QUESTION 51
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 develop an application to identify species of flowers by training a Custom Vision model. You receive images of new flower species.
You need to add the new images to the classifier.
Solution: You add the new images, and then use the Smart Labeler tool.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Explanation
The model need to be extended and retrained.
Note: Smart Labeler to generate suggested tags for images. This lets you label a large number of images more quickly when training a Custom Vision model.
NEW QUESTION 52
You are creating an enrichment pipeline that will use Azure Cognitive Search. The knowledge store contains unstructured JSON data and scanned PDF documents that contain text.
Which projection type should you use for each data type? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Object projection
Object projections are JSON representations of the enrichment tree that can be sourced from any node.
Box 2: File projection
File projections are similar to object projections and only act on the normalized_images collection.
Reference:
https://docs.microsoft.com/en-us/azure/search/knowledge-store-projection-overview
NEW QUESTION 53
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 have an Azure Cognitive Search service.
During the past 12 months, query volume steadily increased.
You discover that some search query requests to the Cognitive Search service are being throttled.
You need to reduce the likelihood that search query requests are throttled.
Solution: You enable customer-managed key (CMK) encryption.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Explanation
Customer-managed key (CMK) encryption does not affect throttling.
Instead, you could migrate to a Cognitive Search service that uses a higher tier.
Note: A simple fix to most throttling issues is to throw more resources at the search service (typically replicas for query-based throttling, or partitions for indexing-based throttling). However, increasing replicas or partitions adds cost, which is why it is important to know the reason why throttling is occurring at all.
Reference:
https://docs.microsoft.com/en-us/azure/search/search-performance-analysis
NEW QUESTION 54
You develop a test method to verify the results retrieved from a call to the Computer Vision API. The call is used to analyze the existence of company logos in images. The call returns a collection of brands named brands.
You have the following code segment.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Yes
Box 2: Yes
If several logs are detected, or the logo image and the stylized brand name are detected as two separate logos, it starts numbering them from the bottom-left corner.
Box 3: No
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-brand-detection
NEW QUESTION 55
You are developing a photo application that will find photos of a person based on a sample image by using the Face API.
You need to create a POST request to find the photos.
How should you complete the request? To answer, drag the appropriate values to the correct targets. Each value 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.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/rest/api/faceapi/face/detectwithurl
https://docs.microsoft.com/en-us/rest/api/faceapi/face/findsimilar
NEW QUESTION 56
You need to create a new resource that will be used to perform sentiment analysis and optical character recognition (OCR). The solution must meet the following requirements:
* Use a single key and endpoint to access multiple services.
* Consolidate billing for future services that you might use.
* Support the use of Computer Vision in the future.
How should you complete the HTTP request to create the new resource? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Box 1: PUT
Sample Request: PUT
https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/test-rg/ Reference:
https://docs.microsoft.com/en-us/rest/api/deviceupdate/resourcemanager/accounts/create
https://www.analyticsvidhya.com/blog/2020/12/microsoft-azure-cognitive-services-api-for-ai-development/
NEW QUESTION 57
You need to develop an automated call handling system that can respond to callers in their own language. The system will support only French and English.
Which Azure Cognitive Services service should you use to meet each requirement? To answer, drag the appropriate services to the correct requirements. Each service may be used once, more than once, or not at all.
You may need to drag the split bat between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Text Description automatically generated with low confidence
Box 1: Text Analytics
The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
Box 2: Translator
Translator is a cloud-based neural machine translation service that is part of the Azure Cognitive Services family of REST APIs. Translator can be used with any operating system and powers many Microsoft products and services used by thousands of businesses worldwide to perform language translation and other language-related operations.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language
https://docs.microsoft.com/en-us/azure/cognitive-services/translator/translator-overview
NEW QUESTION 58
......
Topics of AI-102: Designing and Implementing an Azure AI Solution Exam
Candidates should apprehend the examination topics before they begin of preparation. because it’ll extremely facilitate them in touch the core. Our AI-102 dumps will include the following topics:
1. Analyze solution requirements (25-30%)
Recommend Cognitive Services APIs to meet business requirements
- Select the appropriate data processing technologies
- Select the appropriate AI models and services
- Identify automation requirements
- Select the processing architecture for a solution
- Identify components and technologies required to connect service endpoints
Map security requirements to tools, technologies, and processes
- Identify appropriate tools for a solution
- Identify processes and regulations needed to conform with data privacy, protection, and regulatory requirements
- Identify auditing requirements
- Identify which users and groups have access to information and interfaces
Select the software, services, and storage required to support a solution
- Identify appropriate services and tools for a solution
- Identify integration points with other Microsoft services
- Identify storage required to store logging, bot state data, and Cognitive Services output
2. Design AI solutions (40-45%)
Design solutions that include one or more pipelines
- Select an AI solution that meet cost constraints
- Design a strategy for ingest and egress data
- Design the integration point between multiple workflows and pipelines
- Define an AI application workflow process
- Design pipelines that use AI apps
- Design pipelines that call Azure Machine Learning models
Design solutions that uses Cognitive Services
- Design solutions that use vision, speech, language, knowledge, search, and anomaly detection APIs
Design solutions that implement the Bot Framework
- Integrate bots and AI solutions
- Design bots that integrate with channels
- Design bot services that use Language Understanding (LUIS)
- Integrate bots with Azure app services and Azure Application Insights
Design the compute infrastructure to support a solution
- Identify whether to use a cloud-based, on-premises, or hybrid compute infrastructure
- Identify whether to create a GPU, FPGA, or CPU-based solution
- Select a compute solution that meets cost constraints
Design for data governance, compliance, integrity, and security
- Ensure appropriate governance of data
- Design a content moderation strategy for data usage within an AI solution
- Define how users and applications will authenticate to AI services
- Design strategies to ensure that the solution meets data privacy regulations and industry standards
- Ensure that data adheres to compliance requirements defined by your organization
3. Implement and monitor AI solutions (25-30%)
Implement an AI workflow
- Manage the flow of data through the solution components
- Create solution endpoints
- Define and construct interfaces for custom AI services
- Develop AI pipelines
- Implement data logging processes
- Develop streaming solutions
Integrate AI services with solution components
- Configure prerequisite components to allow connectivity to the Bot Framework
- Implement Azure Search in a solution
- Configure prerequisite components and input datasets to allow the consumption of Cognitive Services APIs
- Configure integration with Cognitive Services
Monitor and evaluate the AI environment
- Maintain an AI solution for continuous improvement
- Monitor AI components for availability
- Identify the differences between expected and actual workflow throughput
- Identify the differences between KPIs, reported metrics, and root causes of the differences
- Recommend changes to an AI solution based on performance data
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