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.

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.

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.

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.

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.

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.

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.