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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 |
| 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 a initial language model by using Language Understanding Service (LUIS) | - create intents and entities based on a schema, and add utterances - create complex hierarchical entities
- train and deploy a model |
| Iterate on and optimize a language model by using Language Understanding | - 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 Language Understanding 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 portal |
| Create a Questions Answering solution using the Language service | - create a question answering project - import questions and answers - 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 |
Implement Knowledge Mining Solutions (15-20%) | |
Microsoft AI-102 (Designing and Implementing a Microsoft Azure AI Solution) Exam is a certification exam that focuses on the skills and knowledge required to design and implement AI solutions using Microsoft Azure. AI-102 exam is designed for individuals who have experience working with various Azure services, including Azure Cognitive Services, Azure Machine Learning, and Azure Bot Service. AI-102 exam tests the candidate's knowledge in designing and implementing AI solutions using these services, as well as their ability to integrate AI solutions into existing systems.
>> AI-102 Reliable Test Notes <<
The example on the right was a simple widget designed Reliable AI-102 Pdf to track points in a rewards program, The pearsonvue website is not affiliated with us, Although computers are great at gathering, manipulating, and calculating raw data, humans prefer their data presented in an orderly fashion. This means keying the shots using a plug-in or specialized New AI-102 Exam Question software application, As is most often the case, you will need to expend some effort to deploy security measures,and when they are deployed, you will incur a level of administrative Valid AI-102 Exam overhead and operational inconvenience, and may also find that there is an impact to network performance.
To take the AI-102 Certification Exam, candidates should have a good understanding of Azure services, experience with data science and machine learning, and knowledge of programming languages such as Python and R. AI-102 exam consists of multiple-choice questions and performance-based tasks that evaluate the candidate's ability to design and implement AI solutions on Azure. Passing this certification exam demonstrates that the candidate has the skills and knowledge required to design and implement AI solutions using Microsoft Azure, which can help them advance their career in the field of AI and machine learning.
NEW QUESTION # 154
You are building a chatbot.
You need to configure the chatbot to query a knowledge base.
Which dialog class should you use?
Answer: B
Explanation:
Comprehensive Detailed Explanation
If a chatbot must query a knowledge base (KB), the Bot Framework uses QnAMakerDialog (inherited into Azure Cognitive Service for Language's Question Answering).
AdaptiveDialog manages complex dialog flows but not specifically KB querying.
ComponentDialog organizes dialogs, but again, not specific for knowledge bases.
SkillDialog is used when invoking another bot (skill), not for KB queries.
The Answer: B. QnAMakerDialog
Reference: Use QnAMakerDialog in Bot Framework
NEW QUESTION # 155
You have the following C# method.
You need to deploy an Azure resource to the East US Azure region. The resource will be used to perform sentiment analysis.
How should you call the method?
Answer: A
Explanation:
To perform sentiment analysis, we specify TextAnalytics, not ContentModerator.
Possible SKU names include: 'F0','F1','S0','S1','S2','S3','S4','S5','S6','S7','S8' Possible location names include: westus, eastus Reference:
https://docs.microsoft.com/en-us/powershell/module/az.cognitiveservices/new- azcognitiveservicesaccount
NEW QUESTION # 156
You have an Azure subscription.
You plan to build an app that will use the Azure Al DALL-E model.
You need to deploy the model.
What should you use?
Answer: C
NEW QUESTION # 157
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
NEW QUESTION # 158
You are planning the product creation project.
You need to build the REST endpoint to create the multilingual product descriptions.
How should you complete the URI? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: api.cognitive.microsofttranslator.com
Translator 3.0: Translate. Send a POST request to:
https://api.cognitive.microsofttranslator.com/translate?api-version=3.0 Box 2: /translate Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/translator/reference/v3-0-translate
NEW QUESTION # 159
......
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