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 Semantic Kernel SDK and establish its significance in the evolving landscape of AI integration. You'll get a clear understanding of what the course covers and how it empowers developers to build intelligent applications. This sets the stage for deeper technical exploration in subsequent modules.

Introduction to Semantic Kernel

In this module, we will build foundational knowledge around key AI concepts including Large Language Models and Generative AI. You'll be introduced to Semantic Kernel, its purpose, and the value it brings to intelligent applications. The section concludes with a business context view of AI agents.

Environment Setup

In this module, we will guide you through configuring your local environment for Semantic Kernel development. You'll explore setup options for both Visual Studio and Visual Studio Code, along with Azure integration. By the end, your environment will be ready for hands-on development.

Build Your Kernel

In this module, we will walk through the process of building a Semantic Kernel from scratch. You'll create the necessary Azure resources and integrate them into a functioning AI app. The section wraps with a hands-on project to solidify your understanding.

Semantic Kernel Plugins

In this module, we will explore the use of plugins to add modular functionality to Semantic Kernel applications. You’ll learn how to craft effective prompts and integrate personas to personalize responses. The hands-on focus culminates in building a semantic career assistant plugin.

Native Functions and Plugins

In this module, we will focus on native functions and how they integrate with plugins for advanced functionality. You’ll create native logic for AI agents and learn how to automate function calls. The goal is to increase the interactivity and intelligence of your applications.

Create Web Chat Assistant

In this module, we will develop a full-stack AI-powered chat assistant using Semantic Kernel. You’ll implement backend services, UI components, and chat history functionality. The section also introduces advanced techniques like RAG to elevate the assistant's contextual accuracy.

Conclusion

In this module, we will wrap up the course by reviewing the main takeaways and reflecting on the journey of building intelligent applications with Semantic Kernel. You'll gain clarity on how to apply what you've learned in practical business contexts. The section also highlights future opportunities for growth.