Semantic Kernel SDK for Intelligent Applications

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Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Learn how to build production-ready AI applications using Microsoft's Semantic Kernel SDK and Azure OpenAI. You'll gain practical experience creating intelligent, context-aware applications that leverage large language models, plugins, Retrieval-Augmented Generation (RAG), and enterprise AI design patterns while following modern .NET development practices. The course begins by introducing generative AI, large language models, and the Semantic Kernel architecture before guiding you through environment setup, Azure OpenAI integration, and your first AI-powered chat application. You'll then explore prompt engineering, reusable prompt templates, built-in plugins, native plugins, automatic function calling, and best practices for developing maintainable AI solutions. Next, you'll build a context-aware ASP.NET Core assistant with authentication, persistent chat history, document management, and intelligent workflows. Finally, you'll implement document processing pipelines, OCR, embeddings, vector-based retrieval, and Retrieval-Augmented Generation (RAG) to create document-aware assistants capable of delivering grounded responses with citations. This course is ideal for .NET developers, software engineers, AI application developers, solution architects, and technical professionals interested in enterprise AI development. Familiarity with C#, ASP.NET Core, and basic cloud concepts is recommended. The course is designed for learners at the Intermediate level. By the end of the course, you will be able to build intelligent applications using Semantic Kernel, integrate Azure OpenAI services, develop reusable AI plugins, implement context-aware assistants with persistent memory, create document processing pipelines, and deploy RAG-powered enterprise solutions that deliver accurate, grounded AI experiences.

Syllabus

Introduction

In this module, we will introduce the course roadmap, learning objectives, and the role of Semantic Kernel in building intelligent AI-powered business applications, providing a clear understanding of what you'll learn and how each section contributes to developing production-ready AI solutions.

Introduction to Semantic Kernel

In this module, we will explore the foundations of generative AI, large language models, and Semantic Kernel while comparing key AI frameworks and understanding how AI agents enable intelligent business applications through scalable and maintainable architectures.

Environment Setup and Starter Solution

In this module, we will set up the complete development environment by installing .NET, configuring Azure OpenAI resources, creating a starter solution, and securely managing application settings to establish a strong foundation for building Semantic Kernel applications.

Building A Simple Chat App With Semantic Kernel

In this module, we will build a functional AI chat application using Semantic Kernel by configuring Azure OpenAI services, implementing conversational workflows, managing chat history, and organizing the application into reusable components following best development practices.

Using Built-In Semantic Kernel and Building Prompt-Based Plugins

In this module, we will explore prompt engineering, Semantic Kernel plugins, reusable prompt templates, personas, and prompt-backed functions to build intelligent AI applications that deliver dynamic, customizable, and business-focused interactions.

Building Native Plugins with Real Business Functions

In this module, we will develop native Semantic Kernel plugins that integrate real business functionality, improve AI tool discoverability, support automatic function invocation, and follow best practices for creating scalable and maintainable AI solutions.

Implementing A Context Aware Chat Assistant in ASP.NET Core

In this module, we will integrate Semantic Kernel into an ASP.NET Core application, build supporting business features, and develop a context-aware chat assistant that leverages application data to deliver more relevant and intelligent user interactions.

Adding User, Chat History, and Contextual Assistance - Persistence

In this module, we will enhance the AI assistant by implementing persistent storage, user authentication, conversation history management, and contextual memory, enabling personalized and continuous AI experiences across user sessions.

Implementing Document Processing Jobs and Features

In this module, we will implement intelligent document processing capabilities by building upload workflows, extracting text from PDFs, processing scanned documents with OCR, and creating preprocessing pipelines that prepare content for AI-powered search and analysis.

Adding RAG and Document Aware Chat Assistant

In this module, we will implement Retrieval-Augmented Generation (RAG) by preparing document embeddings, building semantic search capabilities, retrieving relevant knowledge, grounding AI responses with trusted sources, and creating a document-aware chat assistant that delivers accurate, transparent, and context-rich answers.