Build AI Agents Using Google ADK

As AI systems evolve from single-model interactions to coordinated, autonomous workflows, the ability to build AI agents using Google ADK is becoming a critical skill. Modern applications increasingly rely on multi-agent systems that can reason, collaborate, and execute tasks reliably. Yet most engineers struggle to move beyond simple prototypes. This course is designed to give you a clear, structured path to building production-ready agent systems using Google ADK. I built this course from my work in adaptive AI systems and intelligent architectures, where orchestrating multiple components is often the hardest part of deployment. A recurring pattern I observed was that developers could build individual models, but lacked a framework for coordinating them into reliable agent systems. This course addresses that gap by breaking down how to build AI agents using Google ADK through a systems-first perspective focused on structure, control, and reliability. You’ll start by understanding the core architecture of Google ADK agents and setting up your development environment. From there, you’ll build a single-agent system and extend it into a multi-agent architecture, learning orchestration patterns such as sequential flows, parallel execution, and iterative loops. The course emphasizes hands-on development, evaluation, and deployment, ensuring you can design, test, and scale agent workflows effectively. If you want to build AI agents using Google ADK and move from experimentation to real-world systems, this course provides a clear and practical path to get there.