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Microsoft Azure


Microsoft Certified: Azure AI Engineer Associate (AI-100)

Cycle 1
en journée
Cycle 2
en journée
Module(s)
Jour(s)
Prix
Prix/J
Designing and Implementing a Data Science Solution on Azure (AI-100)
3
* 2400.-
* 800.-

Les cours ont lieu de 9h00 à 12h00 et de 13h30 à 17h00.
Les cours sont dispensés en français sur la base d'une documentation en français si disponible (Fra) ou en anglais (Eng). Si elle est disponible dans les 2 langues, la version française est distribuée sauf demande expresse de l'intéressé. Le prix du cours comprend toute la documentation pédagogique distribuée.
Les cours MOC peuvent être réglés avec les bons de formation offerts par Microsoft.

* Remise de 5 % aux membres ADI, GRI, aux diplômé(e)s ISEIG CP, titulaires du BFI, DFI ou certifié(e)s MCSA, MCSE, MCSD formé(e)s à l’ISEIG


Microsoft Certified: Azure AI Engineer Associate (AI-100)_ISEIG

Microsoft Azure

Ce cours est dispensé en français sur la base d'une documentation pédagogique en anglais

An Azure AI engineer works with Data Engineers and Data Scientists to analyze requirements for AI cloud-based and hybrid AI solutions and implements solutions. They are aware of the various components that make up the Microsoft Azure AI portfolio and related open source frameworks and technologies.

This course help prepare for the exam « AI-100 - Designing and Implementing an Azure AI Solution » to obtain the title « Microsoft Certified: Azure AI Engineer Associate ». Microsoft Certified: Azure AI Engineer Associate (AI-100)_ISEIG

1. Designing and Implementing an Azure AI Solution (Course AI-100)

Overview :

An Azure AI engineer works with Data Engineers and Data Scientists to analyze requirements for AI cloud-based and hybrid AI solutions and implements solutions. They are aware of the various components that make up the Microsoft Azure AI portfolio and related open source frameworks and technologies. The engineer leverages their knowledge to recommend appropriate tools and technologies for a given solution. The engineer is aware of the available data storage options and uses their understanding of cost models, capacity, and best practices to architect and implement AI solutions.

This course teaches the concepts of Azure AI engineering by presenting, and developing, a scenario that creates a customer support Bot that utilizes various tools and services in the Azure AI landscape like language understanding, QnA Maker, and various Azure Cognitive Services to implement language detection, text analytics, and computer vision.

Targuet Audience :

This course is aimed at Cloud Solution Architects, Azure artificial intelligence designers, and AI developers.

Objectives :

After completing this course, students will be able to:

  • Explain the available Cognitive Services on Microsoft Azure and their role in architecting AI solutions.
  • Use the Microsoft Bot Framework and Bot Services.
  • Use the QnA Maker and how to integrate Bots and QnA Maker to build up a useful knowledge base for user interactions.
  • Use LUIS and how to create intents and utterances to support a natural language processing solution.
  • Integrate LUIS with a Bot to better understand the users’ intentions when interacting with the Bot.
  • Integrate Bots and Agents with Azure Cognitive Services for advanced features such as sentiment analysis, image and text analysis, and OCR and object detection.

Prerequisites :

Before attending this course, students must have:

  • Azure Fundamentals
  • Understanding of Azure storage technologies
  • C# Knowledge






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