Develop Generative Ai Apps In Azure Ai Foundry

Build real-world GenAI apps using Azure AI Foundry: model deployment, RAG, fine-tuning, prompt flow & evaluation

What you'll learn

Design and Build AI Solutions Using Azure AI Foundry

Deploy, Fine-Tune, and Integrate Language Models

Implement Retrieval-Augmented Generation (RAG) with Custom Data

Evaluate, Optimize, and Ensure Responsible AI Usage

Leverage Azure AI Foundry SDK for Full-Cycle App Development

Use Prompt Flow to Design and Iterate on Language Model Behavior

Deploy Responsible Generative AI Applications with Governance in Mind

Continuously Improve GenAI Apps Using Evaluation and Feedback Loops

Requirements

Basic Python knowledge, familiarity with cloud concepts (Azure), but no prior AI experience is required

Description

Unlock the power of Generative AI with Azure AI Foundry in this hands-on, end-to-end course designed for developers, data scientists, and AI enthusiasts. Whether you're new to AI or looking to expand your skills with Microsoft's AI stack, this course equips you with practical knowledge and tools to build and deploy production-ready GenAI applications.You’ll start by learning how to plan and set up your Azure environment for AI development, then move on to selecting, deploying, and customizing language models from Azure’s rich model catalog. Through guided labs and real-world examples, you’ll use the Azure AI Foundry SDK to build apps, leverage prompt flow for designing conversational flows, and integrate your own data using Retrieval-Augmented Generation (RAG) techniques.The course also covers advanced topics such as fine-tuning language models, implementing responsible AI practices, and evaluating the performance of your applications using built-in tools in the Azure AI Studio.By the end of the course, you'll be able to confidently design, build, test, and optimize generative AI applications that are reliable, scalable, and ethically sound. No prior machine learning experience is required—just a working knowledge of Python and a passion for innovation.Start building the future of AI with Azure today!

Overview

Section 1: Course Introduction

Lecture 1 Introduction

Lecture 2 Course Prerequisites

Lecture 3 Course Module Walkthrough

Lecture 4 All Resources

Section 2: Plan and prepare to develop AI solutions on Azure

Lecture 5 Module Introduction

Lecture 6 Basics of AI

Lecture 7 Azure AI Services Walkthrough

Lecture 8 Hubs and Projects

Lecture 9 Project Overview - Deploying First LLM Model (GPT-4)

Lecture 10 Developer Tools and SDKs

Lecture 11 Responsible AI Principles and Practices

Section 3: Choose and deploy models from the model catalog in Azure AI Foundry portal

Lecture 12 Module Introduction

Lecture 13 Explore Model Catalog on Azure Foundry

Lecture 14 Deploy a Model to an Endpoint

Lecture 15 Optimizing the Model Performance

Lecture 16 Exercise - Explore, Deploy and Chat with Model

Section 4: Develop an AI app with the Azure AI Foundry SDK

Lecture 17 Module Introduction

Lecture 18 Connecting to Azure AI Foundry Using SDK

Lecture 19 Creating a Chat Client

Lecture 20 Standardize your code

Section 5: Get started with prompt flow to develop language model apps in the AI Foundry

Lecture 21 Module Introduction

Lecture 22 Understand the development lifecycle of a large language model (LLM) app

Lecture 23 Understand core components and explore prompt flow types

Lecture 24 Exercise - Get started with prompt flow

Lecture 25 First LLM Deployment

Section 6: Develop a RAG-based solution with your own data using Azure AI Foundry

Lecture 26 Module Introduction

Lecture 27 Understand how to ground your language model

Lecture 28 Make your data searchable

Lecture 29 Exercise - Create RAG based generative AI app that uses your own data

Lecture 30 Create a RAG-based client application using SDK

Section 7: Fine-tune a language model with Azure AI Foundry

Lecture 31 Module Introduction

Lecture 32 Understand when to finetune a LLM

Lecture 33 Prepare your data to fine tune a chat completion model

Lecture 34 Fine tuning a LLM in Azure AI Foundry- Part -1

Lecture 35 Fine tuning a LLM in Azure AI Foundry- Part -2

Section 8: Implement a responsible generative AI solution in Azure AI Foundry

Lecture 36 Module Introduction

Lecture 37 Map, Measure and Mitigate the Harmful Content

Lecture 38 Exercise - Apply Custom Content Filtering

Section 9: Evaluate generative AI performance in Azure AI Foundry portal

Lecture 39 Module Introduction

Lecture 40 Understand Manual and Automated Method of LLM Model Evaluation

Lecture 41 Exercise - Evaluating GPT-4o Model Performance on Azure AI Foundry

This course is ideal for developers, data scientists, AI enthusiasts, and technical professionals who want to build practical generative AI applications using Azure AI Foundry, regardless of their prior AI experience.