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Designing and Implementing a Microsoft Azure AI Solution

Duration

Course Code

1 day

AI-102T00

About the Course

AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. The course will use C# or Python as the programming language.


Target Audience

Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.


Course Outline


Module 1: Get started with Azure AI Services

Azure AI Services is a collection of services that are building blocks of AI functionality you can integrate into your applications. In this learning path, you'll learn how to provision, secure, monitor, and deploy Azure AI Services resources and use them to build intelligent solutions.


  • Prepare to develop AI solutions on Azure

  • Create and consume Azure AI services

  • Secure Azure AI services

  • Monitor Azure AI services

  • Deploy Azure AI services in containers


Module 2: Create computer vision solutions with Azure AI Vision

Computer vision is an area of artificial intelligence that deals with visual perception. Azure AI Vision includes multiple services that support common computer vision scenarios.


  • Analyze images

  • Image classification with custom Azure AI Vision models

  • Detect, analyze, and recognize faces

  • Read Text in images and documents with the Azure AI Vision Service

  • Analyze video


Module 3: Develop natural language processing solutions with Azure AI Services

Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.


  • Analyze text with Azure AI Language

  • Create question answering solutions with Azure AI Language

  • Build a conversational language understanding model

  • Create a custom text classification solution

  • Custom named entity recognition

  • Translate text with Azure AI Translator service

  • Create speech-enabled apps with Azure AI services

  • Translate speech with the Azure AI Speech service


Module 4: Implement knowledge mining with Azure AI Search

Do you have information locked up in structured and unstructured data sources? Using Azure AI Search, you can extract key insights from this data, and enable applications to search and analyze them.


  • Create an Azure AI Search solution

  • Create a custom skill for Azure AI Search

  • Create a knowledge store with Azure AI Search

  • Enrich your data with Azure AI Language

  • Implement advanced search features in Azure AI Search

  • Build an Azure Machine Learning custom skill for Azure AI Search

  • Search data outside the Azure platform in Azure AI Search using Azure Data Factory

  • Maintain an Azure AI Search solution

  • Perform search reranking with semantic ranking in Azure AI Search

  • Perform vector search and retrieval in Azure AI Search


Module 5: Develop solutions with Azure AI Document Intelligence

In this learning path, discover how Azure AI Document Intelligence solutions can enable you to capture data from typed or hand-written forms. Learn how to build a solution for your custom form types and integrate that solution into an Azure Cognitive Search pipeline.


  • Plan an Azure AI Document Intelligence solution

  • Use prebuilt Document intelligence models

  • Extract data from forms with Azure Document intelligence

  • Create a composed Document intelligence model

  • Build a Document intelligence custom skill for Azure AI search


Module 6: Develop Generative AI solutions with Azure OpenAI Service

Azure OpenAI Service provides access to OpenAI's powerful large language models such as ChatGPT, GPT, Codex, and Embeddings models. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio.


  • Get started with Azure OpenAI Service

  • Build natural language solutions with Azure OpenAI Service

  • Apply prompt engineering with Azure OpenAI Service

  • Generate code with Azure OpenAI Service

  • Generate images with Azure OpenAI Service

  • Implement Retrieval Augmented Generation (RAG) with Azure OpenAI Service

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