Semantic Kernel for .NET: Plugins, Agents & RAG

Build practical AI-powered .NET applications using Microsoft Semantic Kernel, Azure OpenAI, plugins, agents, ASP.NET Core, and retrieval-augmented generation.

Semantic Kernel is Microsoft’s open-source SDK for integrating large language models into real applications. In this course, you will learn how to use Semantic Kernel in C# and .NET to build intelligent application features that can chat, call functions, use plugins, maintain context, process documents, and retrieve grounded answers from your own data.

This is not just a prompt engineering course. You will build a practical AI-enabled business portal using .NET, ASP.NET Core, Azure OpenAI, Semantic Kernel, plugins, chat history, document processing, embeddings, and RAG.

You will start with the fundamentals of generative AI, large language models, and Semantic Kernel. From there, you will configure your .NET development environment, connect to Azure OpenAI, and build your first Semantic Kernel chat flow. You will then refactor your code into reusable services that can be used inside real ASP.NET Core applications.

As the course progresses, you will create prompt-based plugins, native C# plugins, and business functions that Semantic Kernel can invoke automatically. You will learn how plugins help expose existing application logic to AI workflows and how function invocation allows your application to move beyond simple chat responses.

You will then build a context-aware assistant inside an ASP.NET Core application. This assistant will work with portal data, user context, chat history, and persistent conversations. You will also add document upload and processing features, prepare document chunks, generate embeddings, retrieve relevant knowledge, and ground AI responses using retrieval-augmented generation.

By the end of the course, you will understand how Semantic Kernel fits into modern AI application development and how it compares with Microsoft’s broader agent ecosystem. You will also have hands-on experience building AI features that are useful in real business applications.

What you will learn

• Build AI-powered .NET applications using Semantic Kernel

• Connect the Semantic Kernel to Azure OpenAI chat completion services

• Use Semantic Kernel in C# and ASP.NET Core applications

• Create prompt-based plugins and native C# plugins

• Use automatic function invocation to connect AI prompts to application logic

• Build context-aware chat assistants for business portals

• Persist chat history and reload previous conversation context

• Add authenticated user context to AI-assisted workflows

• Process uploaded documents for AI-powered application features

• Prepare document chunks and metadata for retrieval

• Generate embeddings and store searchable knowledge

• Implement retrieval-augmented generation in a .NET application

• Ground AI responses with retrieved content

• Display source references for document-aware answers

• Understand the relationship between the Semantic Kernel, plugins, agents, and the Microsoft Agent Framework

Why take this course?

Many AI demos stop at calling a chat completion API. Real applications need more. They need reusable services, application context, user history, plugins, function calling, document processing, retrieval, and grounded responses.

This course helps .NET developers move beyond simple prompts and start building AI features that fit into real software systems.

You will learn how to connect AI models to your existing C# code, business logic, documents, and ASP.NET Core applications using Semantic Kernel.

Technologies covered

• C#

• .NET 10

• ASP.NET Core

• Semantic Kernel

• Azure OpenAI

• Prompt engineering

• Native plugins

• Prompt-based plugins

• Function invocation

• AI agents

• Chat history

• EF Core

• SQLite

• Document processing

• PDF text extraction

• Embeddings

• Retrieval-augmented generation

• Grounded AI responses

By the end of this course, you will have built a practical Semantic Kernel-powered .NET application that integrates Azure OpenAI, plugins, function invocation, ASP.NET Core, chat history, document processing, embeddings, and retrieval-augmented generation.