Optimize Agent Behavior: Free Google Course
Explore structured instructions, output schemas, model configuration and planning to make agent behavior a clearer development and evaluation problem.
Explore free study options. Check the provider, prerequisites, and certificate details before you begin.
41 courses
Explore structured instructions, output schemas, model configuration and planning to make agent behavior a clearer development and evaluation problem.
Explore agent, model and tool callbacks as observation and control points, with a layered approach to validation and state-aware agent behavior.
Explore built-in tools, MCP integrations and custom functions, then connect tool choices with agent instructions and state-aware behavior.
Explore session state, instruction templating and state namespaces to understand how an agent can use context beyond a conversation transcript.
Explore what ADK contributes beyond prompt engineering, identify its developer tools and compare the main deployment pathways in this short introductory course.
Explore ADK setup, agent identity, Python and YAML definitions, and multiple execution interfaces in Google’s introductory agent-building course.
Understand how AI agents pursue goals, reason and act, then connect those concepts with workplace use cases and the differences from traditional chatbots.
Explore reusable agent skills, custom skill construction and the Google Agents CLI through a free course with step-by-step development and deployment demonstrations.
Explore how MLOps evolves for generative AI and how Google’s Agent Platform fits the workflow in this free thirty-minute Intermediate course.
Explore Agent Assist architecture, Smart Reply, summarization and implementation planning in Google’s free advanced contact center AI course.
Explore generative AI, large language models and healthcare-focused prompt concepts in Google’s free introductory learning course.
Map generative AI applications, agents, platforms, models and infrastructure through Google’s free conceptual course on solution choices.