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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.
The student will learn about the available Cognitive Services on Microsoft Azure and their role in architecting AI solutions.
The student will learn about the Microsoft Bot Framework and Bot Services.
The student will learn about the QnA Maker and how to integrate Bots and QnA Maker to build up a useful knowledge base for user interactions.
The student will learn about LUIS and how to create intents and utterances to support a natural language processing solution.
The student will learn about integrating LUIS with a Bot to better understand the users’ intentions when interacting with the Bot.
The student will learn about integrating Bots and Agents with Azure Cognitive Services for advanced features such as sentiment analysis, image and text analysis, and OCR and object detection.
This course is aimed at Cloud Solution Architects, Azure artificial intelligence designers, and AI developers.
3 Days Course
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