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AI-102T00: Designing and Implementing a Microsoft Azure AI Solution

By Ginger Grant
4 Days
Live Class Recording
February 6, 2024
Course Description

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

Course Outline

Learning Path 1: Prepare for AI engineering

AI Engineers design and develop intelligent solutions that encapsulate artificial intelligence (AI) capabilities. As an aspiring Azure AI Engineer, it's important to understand some of the key foundational concepts on which AI is based, and the various services in Microsoft Azure that you can use to build AI solutions.


  • Prepare to develop AI solutions on Azur3


Learning Path 2: Provision and manage Azure Cognitive Services

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


  • Create and consume Cognitive Services
  • Secure Cognitive Services
  • Monitor Cognitive Services
  • Deploy cognitive services in containers


Learning Path 3: Process and translate text with Azure Cognitive Services

A large volume of the data that applications need to process is in text format. Using Azure Cognitive Services, you can create apps that extract semantic meaning from text and translate it between languages.


  • Extract insights from text with the Language service
  • Translate text with the Translator service


Learning Path 4: Process and Translate Speech with Azure Cognitive Speech Services

Learn how to develop speech-enabled applications by using the Speech service.


  • Create speech-enabled apps with the Speech service
  • Translate speech with the speech service


Learning Path 5: Create a Language Understanding solution with Azure Cognitive 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.


  • Build a Language Understanding model
  • Publish and use a Language Understanding app


Learning Path 6: Build a question answering solution

A common pattern for intelligent apps is to enable users to ask questions using natural language, and receive appropriate answers. This kind of solution brings conversational intelligence to a traditional frequently asked questions (FAQ) publication.


  • Build a question answering solution


Learning Path 7: Create conversational AI solutions

Conversational AI solutions are based on interactions between human users and AI agents called bots. In this learning path, you'll learn how to build bots that can be delivered on Microsoft Azure.


  • Create a bot with the Bot Framework SDK
  • Create a Bot with the Bot Framework Composer


Learning Path 8: Create computer vision solutions with Azure Cognitive Services

Computer vision is an area of artificial intelligence that deals with visual perception. Azure Cognitive Services include multiple services that support common computer vision scenarios.


  • Analyze images
  • Analyze video
  • Classify images
  • Detect objects in images
  • Detect, analyze, and recognize faces


Learning Path 9: Extract text from images and documents

Learn how to implement text extraction solutions with images and documents using form recognizer service's OCR Test Tool, pre-built models, and custom models.


  • Read Text in Images and Documents with the Computer Vision Service
  • Extract data from forms with Form Recognizer


Learning Path 10: Implement knowledge mining with Azure Cognitive Search

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


  • Create an Azure Cognitive Search solution
  • Create a custom skill for Azure Cognitive Search
  • Create a knowledge store with Azure Cognitive Search
  • Enrich a search index using Language Studio
  • Implement advanced search features in Azure Cognitive Search
  • Build an Azure Machine Learning custom skill for Azure Cognitive Search
  • Search data outside the Azure platform in Azure Cognitive Search using Azure Data Factory
  • Maintain an Azure Cognitive Search solution
Course Content
Module 1: Introduction to AI on Azure
Introduction to AI
Getting started with Azure AI services
Using Azure AI Services for enterprise applications
Moduel 2: Develop computer vision solutions with Azure AI Vision
Analyze and manipulate images
Analyze and manipulate images (Continuation after lab)
Detecting Faces with the Azure AI Vision
Custom vision models with Azure AI Vision
Analyze video
Module 3: Develop natural language processing solutions
Analyzing text
Translating text
Build a question answering solution
Custom classification and named entity extraction
Speech recognition, synthesis, and translation
Module 4: Develop Generative AI Solutions with Azure OpenAI Service
Get started with Azure OpenAI Service
Develop apps with Azure OpenAI Service
Apply prompt engineering with Azure OpenAI Service
Use your own data with Azure OpenAI Service
Module 6: Develop solutions with Azure AI Document Intelligence
Use prebuilt Document Intelligence models
Train a custom Document Intelligence model
Train a custom Document Intelligence model (Continuation after lab)