Exam AI-102: Designing and Implementing a Microsoft AzureAI SolutionPlan 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 solutionPlan and configure security for a Cognitive Services solution manage Cognitive Services account keys manage authentication for a resource secure Cognitive Services by using Azure Virtual Network plan for a solution that meets responsible AI principlesCreate 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 ServicesPlan 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) deploy Cognitive Services Containers in Microsoft AzureImplement Computer Vision Solutions (20-25%)Analyze images by using the Computer Vision API retrieve image descriptions and tags by using the Computer Vision API identify landmarks 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 APIExtract text from images extract text from images or PDFs by using the Computer Vision service extract information using pre-built models in Form Recognizer build and optimize a custom model for Form RecognizerExtract 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 by using the Face APIImplement 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 containersImplement 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 custom object 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 containersAnalyze video by using Azure Video Analyzer for Media (formerly 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 customize the Person model used by Video Indexer extract insights from a live stream of video dataImplement Natural Language Processing Solutions (20-25%)Analyze text by using the Text Analytics service retrieve and process key phrases retrieve and process entity information (people, places, urls, etc.) retrieve and process sentiment detect the language used in textManage speech by using the Speech service implement text-to-speech customize text-to-speech implement speech-to-text improve speech-to-text accuracy improve text-to-speech accuracy implement intent recognitionTranslate 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 serviceBuild an initial language model by using Language Understanding Service (LUIS) create intents and entities based on a schema, and then add utterances create complex hierarchical entitieso use this instead of roles train and deploy a modelIterate 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 patternsManage a LUIS model manage collaborators manage versioning publish a model through the 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 portalImplement Knowledge Mining Solutions (15-20%)Implement a Cognitive Search solution create data sources 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 synonym
