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Microsoft AI-102 Exam

Certification Provider: Microsoft
Exam Name: Designing and Implementing a Microsoft Azure AI Solution
Number of questions in our database: 80
Exam Version: Jul. 19, 2021
AI-102 Exam Official Topics:
  • Topic 1: Single Topic

Free Microsoft AI-102 Exam Actual Questions

The questions for AI-102 were last updated On Jul. 19, 2021

Question #1

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.

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Correct Answer: A, B, F, F

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.


https://docs.microsoft.com/en-us/azure/search/index-add-suggesters

Question #2

You need to build a chatbot that meets the following requirements:

Supports chit-chat, knowledge base, and multilingual models

Performs sentiment analysis on user messages

Selects the best language model automatically

What should you integrate into the chatbot?

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Correct Answer: C

Language Understanding: An AI service that allows users to interact with your applications, bots, and IoT devices by using natural language.

QnA Maker is a cloud-based Natural Language Processing (NLP) service that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base (KB) of information.

Text Analytics: Mine insights in unstructured text using natural language processing (NLP)---no machine learning expertise required. Gain a deeper understanding of customer opinions with sentiment analysis. The Language Detection feature of the Azure Text Analytics REST API evaluates text input

Incorrect Answers:

A, B, D: Dispatch uses sample utterances for each of your bot's different tasks (LUIS, QnA Maker, or custom), and builds a model that can be used to properly route your user's request to the right task, even across multiple bots.


https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/overview

Question #3

You have a Video Indexer service that is used to provide a search interface over company videos on your company's website.

You need to be able to search for videos based on who is present in the video. What should you do?

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Correct Answer: A

Video Indexer supports multiple Person models per account. Once a model is created, you can use it by providing the model ID of a specific Person model when uploading/indexing or reindexing a video. Training a new face for a video updates the specific custom model that the video was associated with.

Note: Video Indexer supports face detection and celebrity recognition for video content. The celebrity recognition feature covers about one million faces based on commonly requested data source such as IMDB, Wikipedia, and top LinkedIn influencers. Faces that aren't recognized by the celebrity recognition feature are detected but left unnamed. Once you label a face with a name, the face and name get added to your account's Person model. Video Indexer will then recognize this face in your future videos and past videos.


https://docs.microsoft.com/en-us/azure/media-services/video-indexer/customize-person-model-with-api

Question #4

You need to implement a table projection to generate a physical expression of an Azure Cognitive Search index.

Which three properties should you specify in the skillset definition JSON configuration table node? Each correct answer presents part of the solution. (Choose three.)

NOTE: Each correct selection is worth one point.

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Correct Answer: A, B, E

Defining a table projection.

Each table requires three properties:

tableName: The name of the table in Azure Storage.

generatedKeyName: The column name for the key that uniquely identifies this row.

source: The node from the enrichment tree you are sourcing your enrichments from. This node is usually the output of a shaper, but could be the output of any of the skills.


https://docs.microsoft.com/en-us/azure/search/knowledge-store-projection-overview

Question #5

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?

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