Google Cloud training

Deploy multi-agent systems with Agent Development Kit and Agent Engine

In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Vertex AI Agent Engine to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Engine.

  • Duration: 1 day
  • Languages: English, German
  • Level: Advanced
  • Group size: Up to 16

What you'll learn

  • Build an agent with tools using the Google Agent Development Kit.
  • Establish interaction patterns between multiple agents with parent-child relationships and flows.
  • Utilize features such as session memory, artifact storage, and callbacks.
  • Deploy a multi-agent app to Agent Engine.
  • Query an agent app running on Agent Engine.
  • Evaluate agents within the Agent Development Kit.

Prerequisites

  • Python, gen AI prompt engineering, gen AI tool use

Course outline

Get started with the Agent Development Kit
  • Basics of building an agent in the Agent Development Kit.
Empower Agent Development Kit agents with tools
  • Enhance agents with tools and cover the growing breadth of available tools.
Build multi-agent systems with Agent Development Kit
  • Manage communication and task-sharing between agents through parent-child relationships and flows to enable coordinated responses to queries.
Deploy Agent Development Kit agents to Agent Engine
  • Deploying agent apps to Agent Engine and querying responses.
Evaluate agent systems
  • Evaluate agents within the Agent Development Kit.

Related courses

Generative AI in Production

Traditional MLOps is a set of practices to productionize traditional ML systems for enterprise applications. Generative AI raises new challenges in managing and productionizing applications at scale. The field of generative AI operations seeks to address these new challenges. In this course, you learn about the challenges that arise when deploying and productionizing generative AI-powered applications. You learn how to secure your generative AI-powered applications. Finally, you will discuss best practices for logging and monitoring your generative AI-powered applications in production.

  • Duration: 1 day
  • Languages: English, German
  • Level: Advanced

Vertex Forecasting and Time Series in Practice

This course is an introduction to building forecasting solutions with Google Cloud. You start with sequence models and time series foundations. You then walk through an end-to-end workflow: from data preparation to model development and deployment with Vertex AI. Finally, you learn the lessons and tips from a retail use case and apply the knowledge by building your own forecasting models.

  • Duration: 1 day
  • Languages: English, German
  • Level: Advanced

Agent Observability on Google Cloud

This course provides an applied, intermediate guide to operationalizing AI agents, focusing specifically on achieving production confidence and cost predictability for Gemini-powered workflows on Google Cloud. Participants will learn the methodology and actionable skills necessary to transform non-deterministic agent logic into transparent, auditable, and scalable systems.The course covers core operational disciplines, including mapping the agent's complex thought process (ReAct loops) to Cloud Trace Spans for debugging, implementing Logs-Based Security Metrics for compliance, and setting up actionable alerts and custom dashboards in Cloud Monitoring to proactively control cost overruns and quality drift. The course uses presentations, Visual Walkthroughs, and strategic discussions to ensure effective learning that is directly applicable to the Vertex AI ecosystem

  • Duration: 3 hours
  • Languages: English, German
  • Level: Intermediate

Not sure which course fits?

Book a 30-minute call. We'll look at where your team is, what they need to be able to do, and put together either a specific course date or a tailored learning plan.