AI Engineering Roadmap
for .NET Developers
Learn exactly what to study to become an AI Engineer using C#, ASP.NET Core, Semantic Kernel, Microsoft Agent Framework, MCP, Azure AI, and Retrieval-Augmented Generation.
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Inside the AI Engineering Roadmap
A practical roadmap designed specifically for .NET developers who want to transition into AI Engineering without leaving C#.
AI Fundamentals
Understand how modern AI systems and LLMs actually work.
Prompt Engineering
Write prompts that consistently produce better results.
OpenAI APIs
Integrate GPT models into your ASP.NET Core applications.
Embeddings
Learn semantic search and vector representations.
Vector Databases
Store and retrieve knowledge using Pinecone, Qdrant, or Azure AI Search.
Retrieval-Augmented Generation
Build AI applications that answer using your own data.
Semantic Kernel
Microsoft's official SDK for AI development in .NET.
Microsoft Agent Framework
Build autonomous AI agents using Microsoft's latest framework.
Model Context Protocol (MCP)
Connect AI models with external tools and services.
AI Agents
Design single-agent and multi-agent systems for real workflows.
Azure AI
Deploy secure and scalable AI applications on Azure.
Real Projects
Build chatbots, RAG apps, coding assistants, and AI agents.
Who is this roadmap for?
Complete Learning Path
From AI fundamentals to production-ready AI applications with C#.
Technology Stack
OpenAI, Semantic Kernel, Azure AI, MCP, Agent Framework, Vector Databases, RAG.
8-Week Roadmap
Follow a structured roadmap instead of wasting months watching random YouTube tutorials.