Foundations of Agentic AI

Step into the next generation of artificial intelligence by learning how to build autonomous AI agents using Large Language Models (LLMs) and the Model Context Protocol (MCP). This hands-on course is designed for developers, AI enthusiasts, software engineers, and students who want to create intelligent applications capable of reasoning, planning, using external tools, and interacting with real-world systems.

You’ll begin by understanding the fundamentals of Agentic AI, including how AI agents differ from traditional AI applications and why they are transforming modern software development. Next, you’ll explore the architecture of Large Language Models and learn how they power intelligent decision-making, natural language understanding, and autonomous workflows.

The course then introduces the Model Context Protocol (MCP), a modern standard that enables AI agents to securely connect with external tools, APIs, databases, and enterprise applications. Through practical examples, you’ll learn how MCP enhances interoperability, allowing AI agents to retrieve information, execute actions, and maintain contextual awareness across multiple systems.

Throughout the course, you’ll build real-world projects that demonstrate tool calling, memory management, prompt engineering, retrieval-augmented generation (RAG), workflow automation, multi-agent collaboration, and API integration. You’ll also learn best practices for designing reliable, secure, and scalable AI agent architectures for production environments.

By the end of this course, you’ll have the skills to develop powerful Agentic AI applications using LLMs and MCP, integrate them with external services, automate complex business processes, and build intelligent assistants capable of solving real-world problems. Whether you’re looking to advance your AI career, develop innovative products, or stay ahead in the rapidly evolving AI landscape, this course provides the practical knowledge and hands-on experience needed to succeed.