Training Google Cloud

Training goals

code: G-DADKAE | version: 1.0

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.

 

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.

 

Audience

This course is for:

  • Machine learning engineers
  • Gen AI engineers

Conspect Show list

  • Get started with the Agent Development Kit
    • Topics
      • Basics of building an agent in the Agent Development Kit
    • Objectives
      • Explain how the Agent Development Kit compares to other tools such as the Google Gen AI SDK or LangChain.
      • Describe the parameters used to build an agent in Agent Development Kit.
  • Empower Agent Development Kit agents with tools
    • Topics
      • Enhance agents with tools and cover the growing breadth of available tools.
    • Objectives
      • Discuss the importance of structured docstrings and typing when writing tool functions for agents.
      • Demonstrate the ability to provide tools to an agent.
      • List common and useful tools available for the Agent Development Kit agents, including LangChain tools.
    • Activities
      • Lab: Get started with Agent Development Kit (ADK)
      • Lab: Empower ADK agents with tools
  • Build multi-agent systems with Agent Development Kit
    • Topics
      • Manage communication and task-sharing between agents through parent-child relationships and flows to enable coordinated responses to queries.
    • Objectives
      • Describe the directory structure and naming conventions encouraged by the Agent Development Kit.
      • Demonstrate the ability to create multiple agents and relate them to one another with parent-child relationships.
      • Describe the different flow options and when you might use them.
      • Get responses that have passed through multiple agents.
      • Control content at different points with callbacks.
    • Activities
      • Lab: Build multi-agent systems with ADK
  • Deploy Agent Development Kit agents to Agent Engine
    • Topics
      • Deploying agent apps to Agent Engine and querying responses.
    • Objectives
      • Describe the benefits of deploying agents, especially multi-agent systems, to Agent Engine over self-hosting, such as in Vertex AI online predictions.
      • Demonstrate deploying to Agent Engine.
      • Demonstrate querying a deployed agent app.
    • Activities
      • Lab: Deploy ADK agents to Agent Engine
  • Evaluate agent systems
    • Topics
      • Evaluate agents within the Agent Development Kit.
    • Objectives
      • Evaluate agents within the Agent Development Kit.
      • Use the web interface to view evaluations.
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Additional information

Prerequisites
  • Python, gen AI prompt engineering, gen AI tool use
Difficulty level
Duration 1 day
Certificate

The participants will obtain certificates signed by Google Cloud (course completion).
Trainer

Authorized Google Cloud Trainer

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