This course introduces you to the Google ADK, a powerful framework for building and managing sophisticated AI agents. You will begin by mastering the foundations, including the specific anatomy of an ADK agent and the initial environment setup required for development.
The core of this course is a hands-on project where you will design and build a single-agent setup, then extend it into a highly efficient multi-agent system. You will spend significant time on orchestration, learning how to control complex logic using sequential, parallel, and looping patterns to ensure your agents perform reliably.
The course focuses on practical application, featuring an end-to-end exercise. You will also learn the final steps of a professional AI project: evaluating your agents against rigorous performance criteria and deploying them for real-world use. By the end of this course, you will be equipped to build and orchestrate autonomous agent teams that solve complex problems with confidence.
This course introduces you to the Google ADK, a powerful framework for building and managing sophisticated AI agents. You will b...Show More
WHAT YOU'LL LEARN
An understanding of the Google ADK framework and the core anatomy of an AI agent
Hands-on experience setting up your first basic agent and environment configuration
The ability to design and implement both single-agent and multi-agent using Google ADK
Familiarity with the orchestration patterns, including sequential, parallel, and loop-based workflows within Google ADK
The ability to evaluate agent performance using Google ADK’s specific criteria and scoring methods
Hands-on experience deploying agentic applications into production-ready environments using Google ADK
An understanding of the Google ADK framework and the core anatomy of an AI agent
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Content
2.
Foundations of Google ADK
3 Lessons
Explore the Google ADK for creating scalable AI agents with modular architecture.
3.
Building the Research Assistant
3 Lessons
Develop an efficient AI research assistant through design, implementation, and modular enhancement.
4.
Evaluation and Deployment
3 Lessons
Master agent evaluation and deployment for reliable AI applications.
5.
Orchestrating Workflows
4 Lessons
Master reliable multi-agent workflows through orchestration, enhancing efficiency and robustness.
6.
Exercise
2 Lessons
Master the creation of a hybrid AI system for processing meeting notes.
Certificate of Completion
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