Expert course

Azure AI Agent Service (AI Foundry Hub, Agent Framework)

Work with Azure AI Foundry, Azure OpenAI, RAG, Build multi-agentic systems with Microsoft Agent Framework

Rating: 4.5603 ratings4,323 students19.5 total hours100 lectures
Azure AI Agent Service (AI Foundry Hub, Agent Framework) Expert

Course facts

  • Last updated 04/2026
  • Instructor: Kuljot Singh Bakshi
  • AI agents, automation and connected workflows

What you'll learn

Practical outcomes

  • Build Agents with Azure AI Agent Service
  • Learn About Azure OpenAI and GenAI
  • Learn About Azure AI Foundry
  • Work with Azure AI Foundry SDK

Curriculum

19 sections • 100 lectures • 19h 28m total length

Introduction1 lecture • 4min
  1. Course Introduction03:40
Join the Discord Server!1 lecture • 1min
  1. Join the Discord Server!00:08
GenAI Primer (GA-101)5 lectures • 49min
  1. Intro to GenAI, Agents and Compound AI Systems13:12
  2. What is Azure OpenAI?06:10
  3. Lab: Deploying an Azure OpenAI Resource (Hands-On Lab)03:27
  4. Lab: Chatting With Our Azure OpenAI Model (Hands-On Lab)13:08
  5. Lab: Calling our Azure OpenAI LLM through ChatCompletions API (Hands-On Lab)13:06
Introduction to Azure AI Foundry6 lectures • 51min
  1. Introduction to Azure AI Foundry Studio Hub11:27
  2. Difference(s) between Standalone Projects and Hub-Based Projects12:40
  3. Lab: Navigating the Standalone Projects and Hub Based Projects Studio (Demo)05:35
  4. Lab: Deploying Azure AI Foundry Resource (Hands-On Lab)09:53
  5. Lab: Deploying LLM Model from Model Catalog (Hands-On Lab)05:10
  6. Azure AI Foundry Architecture06:44
Introduction to Azure AI Agents (AAI-101)6 lectures • 1hr 2min
  1. Introduction to Azure AI Agents Service17:29
  2. Lab: Building First Agent through Azure AI Foundry UI (Hands-On Lab)09:47
  3. Introduction to Azure AI Foundry SDK and comparison with Assistants API04:39
  4. Update: Which Azure AI Foundry SDK to use for Labs ?08:25
  5. Lab: Building a Basic Agent with Azure AI Foundry SDK (Hands-On Lab)12:38
  6. Lab: Working With Threads and Azure AI Agent (Hands-On Lab)09:20
Building a Bing WebSearcher Agent2 lectures • 16min
  1. Lab: Deploying a Bing Grounding Resource (Hands-On Lab)04:23
  2. Lab: Building our Agent with the SDK (Hands-On Lab)11:32
Building an Agent with Function Calling4 lectures • 24min
  1. Introduction to Function Calling04:38
  2. What we will be building01:56
  3. Introduction to the OpenWeather API01:40
  4. Lab: Building a Function Calling Agent (Hands-On Lab)15:45
Building an Agent with OpenAPI specified Tools3 lectures • 19min
  1. What are OpenAPI Tools?06:07
  2. What we will be building?02:54
  3. Lab: Building an Azure AI Agent with OpenAPI Tool (Hands-On Lab)10:22
Building a RAG Agent7 lectures • 1hr 18min
  1. The What, Why and How of RAG15:45
  2. What Are Vector Embeddings?16:23
  3. Lab: Working with Vector Embedding engine (Hands-On Lab)07:48
  4. Vector Search With Azure Cognitive Search Theory12:47
  5. RAG Agent Architecture02:12
  6. Lab: Creating Our Azure AI Search Index for RAG (Hands-On Lab)15:12
  7. Lab: Bringing our RAG agent to life with the SDK (Hands-On Lab)08:14
Building a Code Interpreter Agent1 lecture • 11min
  1. Lab: Building a Code Interpreter Agent (Hands-On Lab)11:26
Multiple Tools With a Single Agent2 lectures • 16min
  1. What we will be building?03:14
  2. Lab: Building Our Multi-Tool Agent (Hands-On Lab)12:41
Model Context Protocol (MCP)6 lectures • 1hr 40min
  1. Introduction to MCP14:07
  2. Detailed breakdown of MCP13:06
  3. Claude Desktop and GitHub Copilot on VSCode Installation04:14
  4. Lab 1: Running GitHub MCP Server (Hands-On Demo)23:19
  5. Lab 2: Creating a Weather MCP Server (Hands-On Demo)17:53
  6. Lab 3: Creating an Azure AI Agent Service MCP Server (Hands-On Demo)27:07
Microsoft Agent Framework with Microsoft Foundry14 lectures • 2hr 33min
  1. Introduction to Microsoft Agent Framework18:50
  2. Note: Github Repo for this Module!!!00:03
  3. Lab: Deploying Microsoft Foundry and Walkthrough (Hands-On Lab)13:14
  4. Lab: Deploying OpenAI Model in Foundry and API Call (Hands-On Lab)12:03
  5. Lab: Microsoft Foundry Basic Chat Agent with MAF (Hands-On Lab)17:58
  6. Lab: Local Basic Chat Agent with MAF (Hands-On Lab)08:29
  7. Lab: MCP Tool Agent with MAF (Hands-On Lab)09:56
  8. Lab: Multi-Tool Agent with MAF (Hands-On Lab)08:43
  9. Lab: Getting Started with DevUI to visualize MAF Flows (Hands-On Lab)08:18
  10. Lab: Working with Structured Outputs in MAF (Hands-On Lab)08:02
  11. Lab: Sequential Workflows with MAF (Hands-On Lab)12:17
  12. Lab: Visualizing Sequential Workflow with DevUI (Hands-On Lab)10:54
  13. Lab: Parallel Workflows with MAF (Hands-On Lab)15:31
  14. Lab: Visualizing Parallel Workflows with DevUI (Hands-On Lab)09:08
AI Foundry Local: Local LLMs for the Win!5 lectures • 55min
  1. Introduction to AI Foundry Local12:00
  2. Lab: Onboarding AI Foundry Local to our Device (Hands-On Lab)12:15
  3. Lab: Calling Foundry Local Models via Python Notebook (Hands-On Lab)12:50
  4. Lab: Getting Started with Langchain and AI Foundry Local (Hands-On Lab)10:04
  5. Lab: Web UI for AI Foundry Local (Hands-On Lab)07:43
Evaluating Our Agent9 lectures • 1hr 59min
  1. Introduction to GenAI Evaluation and AI Evaluation SDK11:46
  2. Lab1: Getting Started with the AI Evaluation SDK (Hands-On Lab)14:37
  3. Mechanics of the AI Evaluation SDK: How it Works12:19
  4. Lab: Evaluating our RAG Agent with Groundedness (Hands-On Lab)22:00
  5. Lab: Building a Custom Prompt Evaluator09:57
  6. Introduction to Agent Tracing Capability06:41
  7. Lab: Connecting Application Insights to Azure AI Project (Hands-On Lab)05:52
  8. Lab: Tracing our Agent via Code (Hands-On Lab)20:00
  9. Lab: Building Token Usage Dashboards for Cost Optimization (Hands-On Lab)16:16
Azure Virtual Networking: Securing our AI Agent8 lectures • 1hr 57min
  1. Introduction to Azure Virtual Networking08:58
  2. Introduction to Private and Service Endpoints13:22
  3. Lab: Creating a Private Endpoint (Hands-On Lab)21:07
  4. Introduction to Azure Firewall12:13
  5. Lab: Creating Azure Firewall (Hands-On Lab)26:24
  6. Introduction to Azure DDoS Protection Plan09:58
  7. Introduction to NSGs and ASGs (Network and Application Security Groups)14:15
  8. Lab: Working with NSG (Hands-On Lab)10:22
Azure AI Content Understanding - Multi-Modal RAG10 lectures • 2hr 13min
  1. Introduction to Azure AI Content Understanding20:52
  2. Clarity on Pricing!02:36
  3. Lab: Trying out Content Understanding in Azure Portal (Hands-On Lab)13:23
  4. Lab: Content Understanding with Python Notebook (Hands-On Lab)16:19
  5. Lab: Creating and Testing Custom Analyzer (Hands-On Lab)20:02
  6. Intro to Sustainability RAG Project Architecture04:03
  7. Note: Github Repo for the Project00:03
  8. Lab: Project Infrastructure Set-Up (Hands-On Lab)09:18
  9. Lab: Data Preparation for RAG (Hands-On Lab)32:31
  10. Lab: Building and Running the RAG Pipeline (Hands-On Lab)14:06
Capstone Project 1: Building a Search Engine with Vector Embeddings6 lectures • 1hr 52min
  1. Project Introduction: The Why, What and How?09:22
  2. Introduction to RAG with Azure CosmosDB20:28
  3. RAG with CosmosDB for NoSQL API: Architecture06:03
  4. RAG with CosmosDB for NoSQL API: Hands on Lab29:19
  5. Deploying Resources on Azure (Hands-On Lab)16:12
  6. Running our Project (Hands-On Lab)30:18
Capstone Project 2: Building a Video Generation Multi-Agent System4 lectures • 47min
  1. Capstone Project 2: Introduction06:06
  2. Lab 1: Testing OpenAI Sora in Video Playground (Hands-On Lab)06:24
  3. Lab 2: Testing OpenAI Sora via Python Code (Hands-On Lab)12:45
  4. Lab 3: Video Generator Multi-Agent System (Hands-On Lab)22:11

Who it is for

  • AI Enthusiasts
  • Developers

Course description

Overview

Are you ready to harness the power of Azure AI Agent Service to build intelligent, scalable, and efficient AI-driven solutions? This comprehensive Udemy course is designed to take you from the fundamentals to advanced implementation, enabling you to develop AI agents that automate tasks, enhance decision-making, and integrate seamlessly into business workflows.

What You Will Learn Introduction to Azure AI Agent Service – Understand the core capabilities and architecture of Azure’s AI Agent Service. Building AI-Powered Agents – Learn how to design, develop, and deploy AI agents for various use cases. Integration with Azure AI Services – Leverage services like Azure OpenAI, Cognitive Services, and Machine Learning for enhanced AI capabilities. Agent Orchestration & Automation – Implement AI-driven workflows using Azure AI Studio and orchestration tools. Conversational AI & NLP – Develop AI agents with natural language understanding and conversational capabilities. Security, Compliance & Best Practices – Ensure your AI agents meet security standards and ethical AI principles. Real-World Use Cases – Work on hands-on projects for customer support, business automation, and intelligent decision-making.

Why Take This Course? Azure AI Agent Service is revolutionizing AI application development by providing a powerful, scalable platform for creating intelligent agents. Whether you're a developer, data scientist, or IT professional, this course will give you the expertise to leverage Azure AI Agent Service effectively. By the end of this course, you will have the knowledge and hands-on experience to deploy AI agents that automate workflows, enhance user interactions, and integrate AI into enterprise solutions.

Who This Course is For Developers looking to integrate AI-powered agents into applications. AI & ML engineers who want to leverage Azure AI for automation. IT professionals and solution architects exploring AI-driven automation. Business professionals and entrepreneurs interested in AI applications. Prerequisites Basic understanding of cloud computing and Azure services. Some experience with Python programming languages is helpful. Enthusiasm to explore AI-driven automation! Join this course today and start building intelligent AI agents with Azure AI Agent Service!

Instructor

Kuljot Singh Bakshi

Kuljot Singh Bakshi Instructor at Udemy | Microsoft Certified Trainer Kuljot Singh Bakshi is a dedicated Azure and AI Instructor with a wealth of experience, particularly known for his engaging courses on Udemy. His passion for technology and education has empowered countless students to achieve their goals and advance their careers. He is also a Microsoft Certified Trainer (MCT) and a Microsoft Learn Student Ambassador (MLSA). He is also a C#-Corner MVP, helping the developer community with his contributions. Kuljot is a renowned Udemy instructor with his courses on Azure and AI. He has his courses in the Udemy for Business (UFB) program which is exclusive for only the top 3% percent of all courses on Udemy. Kuljot has received a lot of appraisal and appreciation for his easy-to-understand teaching style and engaging hands-on activities in his courses that bridge theoretical concepts with real world examples. His unique ability to simplify intricate subjects makes him a beloved instructor and mentor to his students. Born with a natural curiosity for innovation, Kuljot's journey into the world of technology began at an early age. Speaking of his academic achievements, Kuljot managed to gain admission as an undergrad major in the department of Environmental Science and Engineering, Indian Institute of Technology (IIT), Bombay; the number one engineering institute of India and known for its rigorous entrance examination, the JEE Advanced, given by over 1.5 million aspirants every year but with only the top 0.3% making it to the prestigious institution. Outside the realm of teaching, Kuljot is often found exploring the latest advancements in AI, continuously seeking to expand his knowledge and stay at the forefront of technological progress. He is also an avid badminton, lawn-tennis and golf enthusiast. In his free time, you might see him on the badminton court, particularly at eventide.