Google Cloud AI Agents: From Foundations to Enterprise Scale
Google Cloud via Coursera Professional Certificate
Overview
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Become an expert in designing, building, and operationalizing intelligent AI agents with Google Cloud’s unified agent stack. This comprehensive, hands-on learning path takes you from the foundational architecture and business use cases of AI agents to active development using Gemini Enterprise and Model Context Protocol (MCP).
You will gain practical experience deploying production-ready agents to scalable environments like Vertex AI Agent Engine and Cloud Run, configuring multi-agent systems, and managing real-time agent memory and state. Finally, you will discover how to orchestrate multi-agent workflows safely across your organization, balancing automated execution with human-in-the-loop oversight. Complete the interactive activities and quizzes to earn developer credentials.
Syllabus
- Course 1: Introduction to AI Agents
- Course 2: Agent Fundamentals
- Course 3: Enterprise Agents and Use Cases
- Course 4: Build Agents with Gemini Enterprise
- Course 5: Build Your First Agent with Gemini Enterprise
- Course 6: Optimize Agent Behavior
- Course 7: Add Agent Capabilities With Tools
- Course 8: Manage Agent Memory and State
- Course 9: Build and Deploy Agents in Production
- Course 10: Deploy Your First Agent
- Course 11: Gen AI Agents: Transform Your Organization
- Course 12: Human-Centered AI
Courses
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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools.
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You’ve built agents with advanced configuration—now give them real-world capabilities. Equip agents with tools that enable searching the web, executing code, querying databases, and performing custom actions. Transform agents from intelligent responders into capable assistants that take action.
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This course introduces the fundamentals of AI agents and explores where agents add value in the real world. It provides a foundation for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior.
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Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems.
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Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK). In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior, taking what you learned in course 1 and applying it to working code.
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Explore the architecture and deployment of multi-agent systems using Google’s Agent Development Kit (ADK) and Google Cloud’s robust infrastructure. You will learn to design hierarchical agent trees and deterministic workflow agents while identifying the ideal hosting environment—from serverless Cloud Run to high-performance GKE—to ensure your AI agents are secure, scalable, and production-ready.
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Take your agents from localhost to production. This course teaches you to deploy ADK agents to Vertex AI Agent Engine and Cloud Run, with optional cross-session memory via Memory Bank.
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Discover how AI agents drive business impact. You’ll map agent types to your KPIs and explore use cases that solve real bottlenecks. Then, learn how Gemini Enterprise empowers you to build and orchestrate the right agents—from no-code to high-code solutions.
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Explore the vital transition from task-driven workflows to human-centric AI orchestration. You will learn to strategically distinguish between augmentation and automation, and how to balance machine efficiency with human intuition.
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Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.
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You've built basic LLM agents that respond to queries—now let's make them stateful. Use session state to build agents that maintain context, remember user preferences, and provide personalized experiences. Transform agents from stateless responders to intelligent assistants.
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You’ve built your first agent—now it’s time to take it further. In this course, you’ll advance your skills by learning how to turn a basic AI agent into a sophisticated, precise assistant—applying advanced instructions, model selection, planning capabilities, and structured output patterns.
Taught by
Google Cloud Training