Join the 5-Day AI Agents Intensive Course with Free gifts from Google

What is the 5-Day AI Agents Intensive Course?

The 5-Day AI Agents Intensive Course is a focused, hands-on learning sprint designed to take you from curiosity to capability in building and deploying AI agents. Think of it as a bootcamp that compresses weeks of reading and trial-and-error into five concentrated days of instruction, labs, and real-world projects.

Who should consider enrolling?

Are you a developer, product manager, student, or curious professional who wants practical skills fast? If you’ve ever wondered how to automate decision-making tasks, orchestrate multi-step workflows, or build conversational assistants that do more than chat, this course is made for you.

Why does this course matter now?

AI agents are becoming the gears that drive modern automation: they’re the factory robots of software, the behind-the-scenes workers that fetch, reason, and act on our behalf. Learning to build them now means you’ll be shaping workflows and products for the near future — not just keeping up, but leading.

How is the five-day format structured?

The course uses an intensive daily rhythm: a focused morning lecture that introduces core concepts, a mid-day guided lab where you build small components, and an afternoon synthesis where you integrate features into a functioning agent. Each day builds on the last, so by Day 5 you have a working prototype and the confidence to iterate further.

What hands-on projects will you build?

Expect to design agents that can: parse instructions, call APIs, maintain context across interactions, and take multi-step actions like booking a meeting or summarizing incoming data. These are practical, product-focused exercises — not toy examples — so you leave with artifacts you can show to teams or use as portfolio pieces.

Which Google technologies and tools are covered?

The course centers on practical stacks: developer tools for agent orchestration, APIs for natural language understanding, and cloud services for deployment and scaling. You’ll learn patterns for integrating model-based reasoning with deterministic services, and how to leverage cloud infrastructure to make agents reliable under load.

What level of prior experience is required?

You don’t need to be a machine learning researcher to benefit. Foundational programming experience and a willingness to tinker are enough. The curriculum scaffolds learning: core concepts are taught clearly, then paired with labs that translate ideas into code.

How does the course teach safety and alignment?

Building agents responsibly is a primary emphasis. Throughout the five days, you’ll learn strategies for defining safe action boundaries, handling ambiguous user intent, and adding human-in-the-loop controls where needed. These practices are treated as essential engineering requirements, not optional extras.

Will there be support after the course ends?

Most intensive courses include follow-up resources: code templates, community forums, and suggested next projects. Graduates leave with a roadmap for continuing skill development and practical ideas for integrating agents into existing products or workflows.

What outcomes can participants expect after completing the course?

By the end, you’ll be able to design, build, and deploy a prototype AI agent that performs meaningful tasks, document its architecture, and explain trade-offs to stakeholders. You’ll have clarity on common pitfalls and the tools to iterate quickly.

How does this course compare to self-study?

Self-study is like learning to swim by reading about water; an intensive course is like being in the pool with an instructor beside you. The compression of knowledge, immediate feedback, and peer troubleshooting accelerate learning in ways that scattered tutorials rarely match.

What are the business applications of AI agents?

From customer support automation and intelligent scheduling to data triage and workflow orchestration, AI agents can reduce repetitive work and surface insights faster. They act as amplifiers for human teams, freeing people to focus on higher-value creative and strategic tasks.

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How should you prepare before Day 1?

A short checklist of readiness includes refreshing basic programming skills, ensuring access to a cloud account for labs, and thinking about a small real-world task you’d love an agent to handle. Coming with a problem in mind will help you get more from the hands-on labs.

What does success look like in the long run?

Success isn’t just a working demo; it’s the ability to iterate on that demo, integrate it into live systems, measure impact, and refine behavior based on user feedback. The course lays the groundwork — the long-term gains come from sustained iteration.