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| Topic | Details |
|---|---|
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 - manage authentication 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, Languages, Speech, Form Recognizer) - deploy Cognitive Services Containers in Microsoft Azure |
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 - 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 API |
| Extract 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 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 by using 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 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 containers |
| Analyze 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 Speech service - customize the 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 Language service | - retrieve and process key phrases - retrieve and 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 - improve text-to-speech accuracy - implement intent recognition |
Microsoft AI-102 (Designing and Implementing a Microsoft Azure AI Solution) is a certification exam that aims to test candidates' knowledge and skills in designing and implementing AI solutions using Microsoft Azure. Designing and Implementing a Microsoft Azure AI Solution certification is intended for professionals who have experience working with Microsoft Azure and are looking to enhance their expertise in AI technologies. Successful completion of this certification exam can lead to career advancement opportunities and recognition as an expert in the field of AI.
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NEW QUESTION # 202
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.
Answer: A,B,C
Explanation:
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.
Reference:
https://docs.microsoft.com/en-us/azure/search/knowledge-store-projection-overview
NEW QUESTION # 203
You have an Azure subscription.
You are building a social media app that will enable users to share images.
You need to ensure that inappropriate content uploaded by the users is blocked. The solution must minimize development effort.
What are two tools that you can use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: C,E
Explanation:
https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/concept-detecting-adult- content
NEW QUESTION # 204
You have an Azure subscription that contains an Azure OpenA1 resource. You configure a model that has the following settings:
* Temperature: 1
* Top probabilities: 0.5
* Max response tokens: 100
You ask the model a question and receive the following response.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth point.
Answer:
Explanation:
Explanation:
NEW QUESTION # 205
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 206
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:
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 # 207
......
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