Building Autonomous AI Agents with Python and Generative AI

Software is evolving from passive tools into active partners that can reason and execute tasks autonomously. This course provides the foundational knowledge and technical skills to build agentic systems from the ground up using Python and Large Language Models. You will gain a deep understanding of how AI agents move beyond simple chat interfaces to perform real-world actions. By focusing on core principles and modern implementation patterns, you will learn to create systems that can plan, use external tools, and refine their own outputs to achieve specific goals. What you'll learn: - Understand the fundamental architecture of autonomous AI agents and agentic workflows - Implement reasoning patterns such as Chain-of-Thought to guide agent decision-making - Build tool-calling capabilities that allow agents to interact with external APIs and data - Apply Retrieval-Augmented Generation (RAG) to provide agents with specialized knowledge - Manage agent memory and state to maintain context across complex, multi-step tasks - Practice writing clean, modern Python code using asynchronous patterns for efficient execution The curriculum begins with essential terminology and the evolution of Generative AI before moving into the practical logic of agent construction and multi-agent coordination. This program is designed for beginners with a basic grasp of Python who want to enter the world of AI development; no prior experience with machine learning is required. Start building the next generation of intelligent software today.