Building Multi-Agent Systems: Google ADK Masterclass

Build & Deploy Multi-Agent AI Systems with Google ADK, Gemini, Docker & Cloud Run — From Architecture to Production

What you’ll learn
Architect enterprise-grade Multi-Agent AI systems using Google’s Agent Development Kit (ADK).
Master the Core ADK Primitives, including Code Execution, Artifact Management, and Long-Term Memory.
Build “WealthPilot” – a stateful multi-agent AI financial advisor that can analyze stocks, executes Python code and generates PDF reports.
Deploy production-ready AI agents to Google Cloud Run and Vertex AI Agent Engine.
Orchestrate Sequential, Parallel, and Loop agent workflows to solve complex multi-step ReAct problems.
Write custom agent tools to give your AI agents the ability to interact with external APIs and live data.

Requirements
Basic understanding of programming (functions, classes, dictionaries, and variable scoping).
A code editor (like VS Code) and basic familiarity with using a computer terminal/command prompt.
No prior AI engineering, machine learning, or complex math experience is required—we will teach you the framework from the ground up.

Description
Are you tired of “toy” AI tutorials that just build simple, stateless chatbots? Are you ready to architect real, autonomous, enterprise-grade multi-agent systems?

Welcome to the definitive masterclass on the Google Agent Development Kit (ADK).

Most developers stop at basic Gemini API calls, never learning how to give their AI long-term memory, custom tools, or secure code execution environments. This keeps them locked out of the high-paying AI Engineering market.

In this course, we skip the fluff and dive straight into professional architecture.

You will systematically master the 11 Core ADK Primitives. You won’t just learn how to write the code; you will learn why the framework routes tasks the way it does, decoupling your agent’s brain (models) from its memory (Session storage) for infinite cloud scalability.

What We Will Build

We learn by building. Throughout the course, you will engineer WealthPilot, an autonomous AI financial firm. You will build a Root Agent that delegates complex tasks to a specialized team

► Stock Analyst — Uses custom tools to fetch live stock prices.

► Portfolio Manager — Uses the Code Execution sandbox to dynamically write and run Python scripts for compound interest calculations.

► Report Generator — Uses Artifact Management to save physical PDF reports to your hard drive.

The Cloud Deployment

In the final section, we will containerize your multi-agent system using Docker, run it locally, and deploy it natively to Google Cloud Run and Vertex AI Agent Engine for production-ready scale.

By the end of this course, you will have

• A fully working multi-agent AI financial system (WealthPilot)

• Mastery of all 11 ADK primitives and when to use each one

• A Dockerized deployment running on Google Cloud Run, and Agent Engine

• The architecture skills to design your own multi-agent systems for any domain

This course is for you if

• You’re a developer who wants to break into AI Engineering

• You’ve built basic chatbots but want to architect production multi-agent systems

• You want to understand the why behind agent orchestration, not just copy-paste code

If you are a developer ready to move beyond prompt engineering and master true Multi-Agent Orchestration, enroll today and let’s start building.

Who this course is for
Developers looking to transition into high-paying AI Engineering and LLM orchestration roles.
Backend engineers wanting to move beyond simple chatbots and learn how to manage long-term agent memory and state.
Tech leads and software architects evaluating Google ADK for scalable, enterprise-grade cloud applications.
Anyone tired of “toy” AI tutorials who wants to build real, autonomous multi-agent systems.