DometrainIntermediate
AI for .NET Developers
Add LLM features to .NET apps by calling local and cloud models through Microsoft.Extensions.AI. You then answer questions from your own documents with RAG and build agents that use tools through MCP and the Microsoft Agent Framework.
- Milestone 1
LLMs from .NET
Call local and cloud LLMs from .NET through Microsoft.Extensions.AI, with streaming and structured output.
- Getting Started: AI for .NET DevelopersCovers prompts, tokens and the .NET AI libraries, then streaming, images, a basic agent and a first look at RAG with the Agent Framework.5h 12m
- From Zero to Hero: Microsoft.Extensions.AI in .NETStays with Microsoft.Extensions.AI and adds local and on-device models, data ingestion, image generation and unit testing LLM code.3h 34m
- Milestone 2
Retrieval over your data
Build a RAG pipeline with embeddings and vector search that answers questions from your own documents.
- Milestone 3
Agents and tools
Build agents that call tools, keep memory and connect to MCP servers, and orchestrate them with the Microsoft Agent Framework.
- Getting Started: AI Agents in C#Builds the agent loop by hand: tool calling, reasoning, memory and context, ending with an MCP server in C#.5h 41m
- Getting Started: Model Context Protocol (MCP)Goes deeper on MCP: clients as well as servers, authentication and trust boundaries, tool design and running a server in production.6h 11m
- Getting Started: Microsoft Agent Framework in .NETOnce you have written the loop by hand, a framework handles tools, structured output, orchestration and observability for systems of agents.5h 48m
Certificate of completionUnlocks after all 6 courses