Agentic Ai Development With Agent Framework, Mcp And .Net
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.00 GB | Duration: 5h 12m
Develop Enterprise Multi-Agent systems using Microsoft Agent Framework, Microsoft Foundry, MCP, Aspire, AG-UI and DevUI
What you'll learn
Master the Microsoft Agent Framework to build autonomous AI agents in .NET
Give AI agents persistent memory and context for meaningful interactions
Create custom function tools by generating JSON schemas directly from C# methods
Design Multi-Agent Workflows including Sequential, Concurrent, and Group Chats
Implement dynamic Group Chat/Debate patterns to intelligently route tasks between agents
Architect Agentic RAG systems using Qdrant Vector Stores and embeddings
Visually test and debug multi-agent JSON payloads and tool calls using DevUI
Integrate the Model Context Protocol (MCP) to securely expose tools to agents
Build Agent-to-Agent (A2A) communications via network-accessible Web APIs
Push interactive, generative UI components directly to frontends using AG-UI
Integrate .NET Aspire to capture OpenTelemetry observability and token counts
Scaffold a complete MinimalAgent microservices backend with AI orchestration
Requirements
Basic to intermediate understanding of C# and the .NET framework (specifically building Web APIs)
No prior AI engineering or machine learning experience is required; we will build your Agentic AI knowledge from the ground up!
Description
"You're a Senior Architect, but AI makes you feel like a Junior again." If you have tried to learn Agentic AI, you have likely noticed a frustrating trend: everything is in Python, or it focuses on simplistic "Hello World" scripts that immediately crumble in a real-world enterprise environment.Welcome to the definitive guide on building production-ready agentic AI systems in the .NET ecosystem. Moving beyond theory, this course focuses on the hands-on development of autonomous multi-agent orchestration for enterprise applications. Powered by the Microsoft Agent Framework, Microsoft Foundry, the Model Context Protocol (MCP), Aspire, AG-UI, DevUI and .NET, you will learn how to build robust AI workflows that solve complex business problems.This course is designed to give you production-grade visibility and control from day one, integrating enterprise-grade AI agent patterns for real-world business workflows.What You Will Master In this comprehensive enterprise course, we move beyond basic prompt engineering into deep architectural implementation natively in C#:Microsoft Agent Framework (MAF): Deep dive into Microsoft's framework for building sophisticated, stateful AI systems, utilizing Microsoft Foundry and Azure OpenAI as your cognitive engines.Multi-Agent Orchestration: Design and implement complex workflow patterns (Sequential pipelines, Concurrent execution, dynamic Handoffs, and Group Chats) using Swarm Intelligence and the WorkflowBuilder.Agentic RAG Systems: Rethink traditional, rigid RAG pipelines. Build intelligent, intent-based retrieval systems using Qdrant vector databases and the TextSearchProvider, allowing the AI to autonomously decide when and how to search your enterprise knowledge.Protocols & Interoperability: Master the bleeding edge of integration: Agent-to-Agent (A2A) network communications, the Model Context Protocol (MCP) for tool exposure, and the AG-UI protocol for generative frontend streaming.Observability & Visual Testing: Achieve production-grade visibility using .NET Aspire and DevUI. Visually track JSON payloads, token usage, agent handoff latencies, and tool calls in real-time.Enterprise Microservices Integration: Scaffold a complete MinimalAgent microservices architecture, learning exactly how to integrate AI agents seamlessly into existing backends and web APIs.Course Roadmap and Structure This curriculum is structured across 4 comprehensive parts, designed to systematically take you from foundational agent anatomy to advanced multi-agent enterprise integration
.NET Developers and Software Engineers looking to transition into AI Engineering and build production-ready agentic systems instead of basic chat wrappers,Software Architects responsible for designing intelligent, autonomous multi-agent architectures using the Microsoft Enterprise Stack,Tech Leads who need to seamlessly integrate complex AI workflows, the Model Context Protocol (MCP), and Agentic RAG into enterprise backends and legacy APIs
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