Microsoft Exam AI-102 Questions Answers Test Simulator

AI-102 Exam Topics

Plan and Manage an Azure Cognitive Services Solution 15-20%

Select the appropriate Cognitive Services resource

• select the appropriate cognitive service for a vision solution
• select the appropriate cognitive service for a language analysis solution
• select the appropriate cognitive Service for a decision support solution
• select the appropriate cognitive service for a speech solution

Plan and configure security for a Cognitive Services solution

• manage Cognitive Services account keys
• manageauthentication for a resource
• secure Cognitive Services by using Azure Virtual Network
• plan for a solution that meets responsible AI principles

Create a Cognitive Services resource

• create a Cognitive Services resource
• configure diagnostic logging for a Cognitive Services resource
• manage Cognitive Services costs
• monitor a cognitive service
• implement a privacy policy in Cognitive Services

Plan and implement Cognitive Services containers

• identify when to deploy to a container
• containerize Cognitive Services (including Computer Vision API, Face API, Text Analytics,Speech, Form Recognizer)

Implement Computer Vision Solutions 20-25%

Analyze images by using the Computer Vision API

• retrieve image descriptions and tags by using the Computer Vision API
• identifylandmarks and celebrities by using the Computer Vision API
• detect brands in images by using the Computer Vision API
• moderate content in images by using the Computer Vision API
• generate thumbnails by using the Computer Vision API

Extract text from images

• extract text from images by using the OCR API
• extract text from images or PDFs by using the Read API
• convert handwritten text by using Ink Recognizer
• extract information from forms or receipts by using the pre-built receipt model in FormRecognizer
• build andoptimize a custom model for Form Recognizer

Extract facial information from images

• detect faces in an image by using the Face API
• recognize faces in an image by using the Face API
• analyze facial attributes by using the Face API
• match similar faces byusing the Face API

Implement image classification by using the Custom Vision service

• label images by using the Computer Vision Portal
• train a custom image classification model in the Custom Vision Portal
• train a custom image classification model by using the SDK
• manage model iterations
• evaluate classification model metrics
• publish a trained iteration of a model
• export a model in an appropriate format for a specific target
• consume a classification model from a client application
• deploy image classification custom models to containers

Implement an object detection solution by using the Custom Vision service

• label images with bounding boxes by using the Computer Vision Portal
• train a custom object detection model by using the Custom Vision Portal
• train a customobject detection model by using the SDK
• manage model iterations
• evaluate object detection model metrics
• publish a trained iteration of a model
• consume an object detection model from a client application
• deploy custom object detection models to containers

Analyze video by using Video Indexer

• process a video
• extract insights from a video
• moderate content in a video
• customize the Brands model used by Video Indexer
• customize the Language model used by Video Indexer by using the Custom Speechservice
• customizethe Person model used by Video Indexer
• extract insights from a live stream of video data

Implement Natural Language Processing Solutions 20-25%

Analyze text by using the Text Analytics service

• retrieve and process key phrases
• retrieveand process entity information (people, places, urls, etc.)
• retrieve and process sentiment
• detect the language used in text

Manage speech by using the Speech service

• implement text-to-speech
• customize text-to-speech
• implement speech-to-text
• improve speech-to-text accuracy

Translate language

• translate text by using the Translator service
• translate speech-to-speech by using the Speech service
• translate speech-to-text by using the Speech service

Build an initial language model by using Language UnderstandingService (LUIS)

• create intents and entities based on a schema, and then add utterances
• create complex hierarchical entitiesouse this instead of roles
• train and deploy a model

Iterate on and optimize a language model by using LUIS

• implement phrase lists
• implement a model as a feature (i.e. prebuilt entities)
• manage punctuation and diacritics
• implement active learning
• monitor and correct data imbalances
• implement patterns

Manage a LUIS model

• manage collaborators
• manage versioning
• publish a model throughthe portal or in a container
• export a LUIS package
• deploy a LUIS package to a container
• integrate Bot Framework (LUDown) to run outside of the LUIS portal

Implement Knowledge Mining Solutions 15-20%

Implement a Cognitive Search solution

• create datasources
• define an index
• create and run an indexer
• query an index
• configure an index to support autocomplete and autosuggest
• boost results based on relevance
• implement synonyms

Implement an enrichment pipeline

• attach a Cognitive Services account to askillset
• select and include built-in skills for documents
• implement custom skills and include them in a skillset

Implement a knowledge store

• define file projections
• define object projections
• define table projections
• query projections

Manage a Cognitive Search solution

• provision Cognitive Search
• configure security for Cognitive Search
• configure scalability for Cognitive Search

Manage indexing

• manage re-indexing
• rebuild indexes
• schedule indexing
• monitor indexing
• implement incremental indexing
• manageconcurrency
• push data to an index
• troubleshoot indexing for a pipeline

Implement Conversational AI Solutions 15-20%

Create a knowledge base by using QnA Maker

• create a QnA Maker service
• create a knowledge base
• import a knowledge base
• train and test a knowledge base
• publish a knowledge base
• create a multi-turn conversation
• add alternate phrasing
• add chit-chat to a knowledge base
• export a knowledge base
• add active learning to a knowledge base
• manage collaborators

Design and implement conversation flow

• design conversation logic for a bot
• create and evaluate *.chat file conversations by using the Bot Framework Emulator
• add language generation for a response
• design and implement adaptive cards

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