Multi-Agent Systems with Google ADK and Vertex AI

Overview

Master multi-agent workflows using Google ADK and Vertex AI to build distributed systems with specialized agents, orchestration patterns, and A2A communication protocols.

Syllabus

• Introduction to Multi-Agent Systems
Overview of Multi-Agent Systems (MAS)
Key Concepts: Agents, Environments, and Interactions
Applications and Use Cases
• Fundamentals of Google ADK
ADK Architecture and Components
Setting Up the Development Environment
Creating and Configuring Agents with ADK
• Introduction to Vertex AI
Vertex AI Overview and Capabilities
Integration of Vertex AI with MAS
Deploying ML Models in Vertex AI for MAS
• Agent Orchestration Patterns
Centralized vs. Decentralized Orchestration
Workflows and Task Distribution
Designing Efficient Agent Interactions
• A2A Communication Protocols
Protocols for Agent-to-Agent Communication
Implementing A2A in Google ADK
Ensuring Reliable Messaging and Data Exchange
• Building Distributed Systems with ADK and Vertex AI
Designing Distributed Architectures
Implementing Scalable Multi-Agent Workflows
Monitoring and Optimization
• Hands-On Labs and Projects
Practical Exercises with Google ADK
Case Studies using Vertex AI in MAS
Final Project: Designing and Implementing a Multi-Agent System with ADK and Vertex AI
• Best Practices and Advanced Topics
Security and Privacy in MAS
Performance Tuning and Optimization
Emerging Trends in Multi-Agent Systems
• Course Review and Assessment
Recap of Key Concepts and Techniques
Final Assessment
Q&A and Future Directions in Multi-Agent Systems

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Subjects

Artificial Intelligence