Build Autonomous AI Agents with Gemini and Docker

AI agents are transforming how we automate repetitive tasks and boost business productivity. If you want to move beyond simple chatbots and build self-directing systems that can execute complex workflows, containerized AI agents are the way forward. In this beginner-friendly written course, you will learn the fundamental principles of autonomous AI agents. You will discover how to leverage the Gemini API for intelligent decision-making and package your applications securely using Docker. By the end of this course, you will have a clear understanding of agentic workflows and how to run them reliably in isolated container environments. What you'll learn: - Understand the core architecture and design patterns of autonomous AI agents. - Configure the Gemini API to handle complex prompts and structured outputs. - Containerize your AI applications using Docker for consistent deployment. - Implement secure environment variable management for API keys and credentials. - Apply agentic reasoning loops to allow your system to plan and execute tasks. - Troubleshoot and debug containerized AI workflows. The course starts with foundational definitions of AI agents and containerization basics. You will then progress through step-by-step written explanations and code examples that guide you from writing your first agent script to packaging the entire application inside a Docker container. This course is designed for developers, tech enthusiasts, and productivity hackers who are new to AI agents and Docker. No prior experience with containerization or LLM APIs is required. Start reading today to build and deploy your very first autonomous AI agent.