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

• Introduction to AI

• Considerations for responsible AI

• Azure Machine Learning

• Introduction to azure ai services

• Azure AI services rest API and SDK

• Considerations of azure ai services security

• Monitor azure ai services

• Deploy azure ai services in containers

• Exercise: Get started with azure ai services

• Exercise: Manager azure ai service security

• Exercise: Monitor azure ai services

• Exercise: Use azure ai services container

• Azure AI Vision – Image Analysis

• Image analysis API and options

• Azure AI vision OCR

• Face detection, analysis and recognition

• Custom azure ai vision model for classification and object detection

• introduction to video indexer for video analysis

• Exercise: Explore features in Vision Studio

• Exercise: Analyze Images with Azure AI Vision

• Exercise: Read text in images

• Exercise: Detect and analyze faces

• Exercise: Classify Images with Azure AI Vision custom model

• Exercise: Analyze the video using video indexer

• Introduction to azure ai language service for language analysis

• Text translation using translator service

• Introduction to question and answering

• Creating a knowledge base

• Introduction to the language understanding

• Custom text classification

• Introduction to the speech service

• Introduction to speech synthesis markup language

• Translating speech to text

• Exercise: Analyze text

• Exercise: Translate text

• Exercise: Create a question and answering solution

• Exercise: Create a conversational language understanding app

• Exercise: Recognize and Synthesize Speech

• Introduction to generative ai

• Introduction to azure open-ai studio

• Various types of models in azure OpenAI

• Various Api's in azure OpenAI

• Testing models in azure OpenAI studio playground

• Integrating Azure OpenAI into your app

• Using the Azure OpenAI REST API: completion, chat completion

• Prompt engineering in azure OpenAI

• Implement Retrieval Augmented Generation (RAG) with Azure Open AI Service

• Exercise: Provision an Azure OpenAI resource in Azure

• Exercise: Get started with Azure OpenAI Service

• Exercise: Integrate Azure OpenAI into your app

• Exercise: Utilize prompt engineering in your app Exercise: Implement Retrieval Augmented Generation

(RAG) with Azure OpenAI Service

• Introduction to the azure ai search

• Core Components of an AI Search Solution

• How an Enrichment Pipeline Works

• Introduction to Custom Skills

• What is a Knowledge Store?

• Implementing a Knowledge Store

• Exercise – Create an Azure Cognitive Search Solution

• Exercise – Create a Custom Skill for Azure AI Search

• Introduction to Document Intelligence Service

• Prebuilt models in document intelligence service

• Custom models in document intelligence service

• Exercise – Use prebuilt Document Intelligence models

• Exercise – Extract Data from Form

• Get started with AI agent development on Azure

• Develop an AI agent with Azure AI Agent Service

• Integrate custom tools into your agent

• Develop an AI agent with Semantic Kernel

• Add plugins to Azure AI agent

• Orchestrate a multi-agent solution using Semantic Kernel

• Exercise - Develop a multi-agent solution

• Exercise - Develop an Azure AI agent with the Semantic Kernel SDK

• Exercise - Build an AI agent