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Azure AI Engineer Associate

AI-102: Azure AI Engineer Associate, you build, manage, and deploy AI solutions that leverage Azure AI. Your responsibilities include participating in all phases of AI solutions development, including: Requirements definition and design, Development, Deployment, Integration, Maintenance, Performance tuning, Monitoring.

1. Select the appropriate Azure AI service

  • Select the appropriate service for a computer vision solution
  • Select the appropriate service for a natural language processing solution
  • Select the appropriate service for a decision support solution
  • Select the appropriate service for a speech solution
  • Select the appropriate service for a generative AI solution
  • Select the appropriate service for a document intelligence solution
  • Select the appropriate service for a knowledge mining solution

  • Plan for a solution that meets Responsible AI principles
  • Create an Azure AI resource
  • Determine a default endpoint for a service
  • Integrate Azure AI services into a continuous integration and continuous delivery (CI/CD) pipeline
  • Plan and implement a container deployment

  • Configure diagnostic logging
  • Monitor an Azure AI resource
  • Manage costs for Azure AI services
  • Manage account keys
  • Protect account keys by using Azure Key Vault
  • Manage authentication for an Azure AI Service resource
  • Manage private communications

  • Implement a data monitoring solution with Azure AI Metrics Advisor
  • Implement a text moderation solution with Azure AI Content Safety
  • Implement an image moderation solution with Azure AI Content Safety

  • Select visual features to meet image processing requirements
  • Detect objects in images and generate image tags
  • Include image analysis features in an image processing request Interpret image processing responses
  • Extract text from images using Azure AI Vision
  • Convert handwritten text using Azure AI Vision

  • Choose between image classification and object detection models
  • Label images
  • Train a custom image model, including image classification and object detection
  • Evaluate custom vision model metrics
  • Publish a custom vision model
  • Consume a custom vision model

  • Use Azure AI Video Indexer to extract insights from a video or live stream
  • Use Azure AI Vision Spatial Analysis to detect presence and movement of people in video

  • Extract key phrases
  • Extract entities
  • Determine sentiment of text
  • Detect the language used in text
  • Detect personally identifiable information (PII) in text

  • Implement text-to-speech
  • Implement speech-to-text
  • Improve text-to-speech by using Speech Synthesis Markup Language (SSML)
  • Implement custom speech solutions
  • Implement intent recognition
  • Implement keyword recognition

  • Translate text and documents by using the Azure AI Translator service
  • Implement custom translation, including training, improving, and publishing a custom model
  • Translate speech-to-speech by using the Azure AI Speech service
  • Translate speech-to-text by using the Azure AI Speech service
  • Translate to multiple languages simultaneously

  • Create intents and add utterances
  • Create entities
  • Train, evaluate, deploy, and test a language understanding model
  • Optimize a language understanding model
  • Consume a language model from a client application
  • Backup and recover language understanding models

  • Create a question answering project
  • Add question-and-answer pairs manually
  • Import sources
  • 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
  • Create a multi-language question answering solution

  • Provision a Cognitive Search resource
  • Create data sources
  • Create an index
  • Define a skillset
  • Implement custom skills and include them in a skillset
  • Create and run an indexer
  • Query an index, including syntax, sorting, filtering, and wildcards
  • Manage Knowledge Store projections, including file, object, and table projections

  • Provision a Document Intelligence resource
  • Use prebuilt models to extract data from documents
  • Implement a custom document intelligence model
  • Train, test, and publish a custom document intelligence model
  • Create a composed document intelligence model
  • Implement a document intelligence model as a custom Azure Cognitive Search skill

  • Provision an Azure OpenAI Service resource
  • Select and deploy an Azure OpenAI model
  • Submit prompts to generate natural language
  • Submit prompts to generate code
  • Use the DALL-E model to generate images
  • Use Azure OpenAI APIs to submit prompts and receive responses

  • Configure parameters to control generative behavior
  • Apply prompt engineering techniques to improve responses
  • Use your own data with an Azure OpenAI model
  • Fine-tune an Azure OpenAI model


Fees Structure : 15500 INR / 190 USD
Total No of Class : 102 Video Class
Class Duration : 48:30 Working Hours
Download Feature : Download Avalable
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

Brochure       Buy Now       Sample Demo

Fees Structure : 30000 INR / 365 USD
Class Duration : 60 Days
Class Recording : Live Class Recording available
Class Time : Monday to Firday 1.5 hours per day / Weekend 3 Hours per day
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

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