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.
Applied Learning Project
Through hands-on activities, coding exercises, and quizzes, learners will build and operationalize real-world AI agents using Google Cloud's unified agent stack. You will set up Gemini Enterprise development environments, build agents using both Python code and YAML configurations, and optimize behavior with advanced instructions and structured outputs. Practical exercises guide you through equipping agents with real-world tools, managing session state, and configuring long-term memory with Memory Bank. Finally, guided activities walk you through deploying production-ready agents to Vertex AI Agent Engine and Cloud Run while applying human-centered AI governance.
