AI Agents with Semantic Kernel & Gemini

Master Basics of Semantic Kernel: Build Python AI Agents using Google Gemini, Custom Plugins, and Function Calling.

Unlock the power of "Agentic AI" by combining Microsoft’s Semantic Kernel with Google’s Gemini Flash model. Most AI tutorials stop at simple chatbots. This course takes you further. You will learn how to build a functional AI Smart Home Agent that doesn't just talk—it acts. Using Python, you will bridge the gap between Large Language Models (LLMs) and real-world logic.

What makes this course unique? We focus on the Semantic Kernel (SK), a powerful SDK that allows you to integrate AI into your applications professionally. You will learn the industry-standard way to manage prompts, handle chat history, and, most importantly, create Custom Plugins.

In this hands-on journey, we will cover:

1. Environment Strategy: Setting up VS Code and securing your Gemini API keys.

2. Professional Debugging: Implementing a color-coded logging system so you can see exactly how the AI "thinks" and which functions it triggers.

3. Plugin Development: Writing Python code that the AI can execute to control devices (like our Smart Light simulation).

4. Autonomous Function Calling: Configuring the kernel to automatically decide which tool to use based on the user's natural language.

5. State Management: Using Chat History to ensure your agent remembers the context of the conversation.

By the end of this course, you will have a working template for building AI agents that can be applied to customer support, data analysis, or IoT automation. Whether you are a developer or an AI enthusiast, these skills will put you at the forefront of the AI revolution.