Scaling Data Science with Agents: Free Google Course
Explore the Data Science Agent, the Context–Task–Constraints prompting framework and critical review of agent-assisted analysis in Google’s intermediate course.
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Explore the Data Science Agent, the Context–Task–Constraints prompting framework and critical review of agent-assisted analysis in Google’s intermediate course.
Explore models, reasoning loops, tools and retrieval in generative-AI agents, then connect the technical pieces with organizational planning and use cases.
Explore how multiple agents can connect business information, marketing work and cross-system actions through Google’s introductory workflow examples.
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.
Compare GPU workload deployment on Compute Engine and GKE, including infrastructure choices for AI inference.
Get oriented to GKE network design questions and the Google Cloud Architecture Center in this short free course.