Overview

This Nanodegree program teaches advanced prompting techniques for effective LLM reasoning using Google Gemini, including chain-of-thought and feedback loops. You will then learn how to design and implement complex agentic workflows using the Agent Development Kit (ADK) and common patterns like routing and parallelization. You will also learn how to empower agents by integrating external tools, APIs, databases, web search, and RAG, while implementing memory management and observability. The program concludes with designing, building, and orchestrating multi-agent systems where specialized agents collaborate to solve complex problems using ADK, the Agent2Agent (A2A) protocol, and multi-agent RAG with Vertex AI Search.

Syllabus

Prompting for Effective LLM Reasoning with Gemini

This course equips you with strategies to harness the power of Google Cloud’s Gemini for agentic AI development. You will explore the fundamentals of agentic AI and advanced prompting techniques such as role-based prompting and chain-of-thought (CoT) prompting. The course covers prompt instruction refinement and chaining methods for enhancing reasoning capabilities. Additionally, you will learn to implement feedback loops specifically for code generation tasks. For the final project, you will design a Legal Intelligence AI System, applying learned techniques to solve real-world legal challenges.

Agentic Workflows with Google ADK

In "Agentic Workflows with ADK," learners will explore the principles of creating intelligent, automated workflows using the Google Agent Development Kit and Vertex AI Gemini. The course begins by defining agentic workflows and progresses into hands-on lessons for modeling and implementing various workflow patterns, including prompt chaining, routing, and parallelization. Participants will also tackle more complex patterns like evaluator-optimizer and orchestrator-worker workflows. The course culminates in a project where students will create an AI Research Assistant, applying their skills to develop a sophisticated agent-based system. Ideal for those interested in advancing their knowledge of AI and workflow automation.

Building Agents with Google ADK and Vertex AI

This course guides you through building intelligent agents using the Agent Development Kit (ADK) and Google Cloud technologies. You will start with tool definition and agent tool usage, then progress through structured outputs, state management, and memory systems (short and long-term). The course covers secure API integration, database interaction via MCP, web search with grounding, and Retrieval Augmented Generation (RAG). You'll explore multi-agent architectures and implement observability through distributed tracing. For the final project, you'll build Betty's Bird Boutique Customer Service Agent that answers bird- and store-related questions.

Multi-Agent Systems with Google ADK and Vertex AI

This course teaches the skills to design and implement effective multi-agent workflows using the Google ADK framework and Vertex AI Gemini. Starting with foundational architecture patterns, you'll progress through implementation, orchestration (sequential and parallel), custom routing logic, explicit state management, and distributed A2A communication. You'll learn to integrate external databases, implement multi-agent RAG with vector search, and build microservices-based architectures. The final project involves building a distributed banking system with multiple specialized agents communicating via A2A protocol.