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.
What you will 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
Target audience
- Machine learning engineers, Gen AI engineers
Training Program
5 modules to master the fundamentals
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.
Topics covered
- →Basics of building an agent in the Agent Development Kit.
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.
Topics covered
- →Enhance agents with tools and cover the growing breadth of available tools.
Activities
Lab: Get started with Agent Development Kit (ADK)
Lab: Empower ADK agents with tools
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.
Topics covered
- →Manage communication and task-sharing between agents through parent-child relationships and flows to enable coordinated responses to queries.
Activities
Lab: Build multi-agent systems with ADK
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.
Topics covered
- →Deploying agent apps to Agent Engine and querying responses.
Activities
Lab: Deploy ADK agents to Agent Engine
Objectives
- Evaluate agents within the Agent Development Kit.
- Use the web interface to view evaluations.
Topics covered
- →Evaluate agents within the Agent Development Kit.
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Guided Labs — Guided practical exercises on software, hardware, or technical environments.
- Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Train multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote