ADK Masterclass – Hands-On Series
Overview
A free, hands-on series to master Google's Agent Development Kit (ADK). Learn to build, evaluate, and deploy AI agents from zero to production through step-by-step tutorials.
View Code on GitHubModules
Open-source toolkit for building, evaluating, and deploying AI agents.
1. Getting Started
Introduction to ADK – Overview, environment setup, and your first agent.
2. Setting Up Agents (Web, CLI, Programmatic)
Different ways to create and interact with agents.
3. Build Agents with Visual Builder
Build agents with Visual Builder.
Learn how to design, compose, and scale agents.
4. Building LLM Agents
Build intelligent, model-powered agents.
5. Workflow Agents (Sequential, Loop, Parallel)
Create dynamic task flows with sequential, loop, and parallel workflows in Google ADK.
6. Multi-Agent Systems
Compose multiple agents into hierarchical systems for complex applications using agent composition patterns.
Extend your agents with APIs, services, and custom tools.
7. Built-in Tools - Google Search, Code Executor
Explore the Google Search and Code Executor built-in tools.
8. Built-in Tools - Vertex AI RAG Engine
Learn how to use the Vertex AI RAG Engine built-in tool to create grounded agents with your own data.
9. Built-in Tools - Vertex AI Search
Build agents that can search across your enterprise data using the Vertex AI Search built-in tool.
10. Custom Function Tools
Build custom functions that add specialized capabilities to your agents beyond built-in tools.
11. OpenAPI Tools with Authentication
Transform OpenAPI-defined APIs into agent tools and configure authentication for secure access.
12. Multi-Tool Agents
Build agents that leverage multiple tools together to accomplish complex tasks.
13. Third Party Tools (GitHub, Firecrawl)
Connect your agents to external services for version control and web content extraction.
14. MCP Toolbox for Databases - PostgreSQL
Connect your ADK agents to PostgreSQL databases using MCP Toolbox for enterprise-grade data access.
Enable context and multi-agent collaboration.
15. Model Context Protocol (MCP)
Understanding the Model Context Protocol - architecture, connection types, and production patterns.
Understand internal mechanisms for robust, scalable agent design.
16. Session, State & Memory
Manage conversation history, state, and memory for multi-turn interactions.
17. Context Management
Optimize agent performance with context caching and compression techniques.
18. Callbacks
Intercept and customize agent behavior at various execution points.
19. Artifacts
Store and manage files, images, and data produced by agents.
20. Events
Understand the event system for real-time streaming and debugging.