Join the 5-Day AI Agents Intensive Course with Google
Introduction
Artificial Intelligence (AI) has become one of the most powerful technologies of our time, shaping how we work, communicate, and solve problems. From virtual assistants like Google Assistant to advanced automation systems, AI agents are at the heart of this transformation. To help people learn these powerful skills, Google has launched the 5-Day AI Agents Intensive Course, an accelerated online learning program focused on understanding, designing, and building AI agents using Google’s cutting-edge tools and platforms.
This course is designed for students, developers, and professionals who want to learn AI practically, even without deep coding or data science experience. Over five days, learners go through a structured journey from the basics of AI agents to hands-on projects using Google’s AI ecosystem, including Gemini, Vertex AI, and other automation tools.
Course Structure
The 5-Day AI Agents Intensive Course is designed to deliver maximum learning in a short time. Each day focuses on a key concept, with interactive lessons, coding demos, and assignments. Here’s how it’s typically structured:
-
Duration: 5 days (intensive format)
-
Mode: Online (live or recorded sessions)
-
Daily Schedule: 1 to 2 hours of sessions + practice time
-
Content Type: Lectures, labs, projects, and quizzes
-
Final Output: A mini-project demonstrating your AI agent
Learners can attend live sessions or watch the recordings later. All sessions are conducted in an easy-to-follow manner, making them suitable even for beginners.
What is an AI Agent?
Before diving deeper, it’s important to understand what an AI agent actually is.
An AI agent is a program or system capable of perceiving its environment, analyzing information, and taking intelligent actions to achieve specific goals. It can communicate, make decisions, and complete tasks automatically — often mimicking human reasoning or conversation.
-
mini) or ChatGPT
-
Virtual assistants like Google Assistant or Siri
-
Automation systems that respond to data or user actions
In this course, learners don’t just learn theory — they actually build and test their own AI agents using Google’s AI tools.
Day-by-Day Learning Breakdown
Day 1: Introduction to AI Agents and Google AI Ecosystem
-
Overview of artificial intelligence and its real-world impact
-
Understanding what AI agents are and how they function
-
Introduction to Google AI tools, including Vertex AI, Gemini, and Google Cloud AI
-
Setting up your Google Cloud environment
-
Basic hands-on activity: exploring AI demos and APIs
By the end of Day 1, learners understand the overall AI landscape and have a clear idea of the tools they will use.
Day 2: Core Concepts – How AI Agents Think and Learn
-
Understanding the architecture of AI agents
-
How agents process input and produce output
-
Introduction to prompt engineering and reasoning
-
Basics of machine learning models used in AI agents
-
Activity: Building a simple rule-based agent
This day focuses on the logic and decision-making processes that power AI systems.
Day 3: Building Your First AI Agent Using Gemini
-
Introduction to Gemini (Google’s advanced AI model)
-
Understanding text, image, and multi-modal inputs
-
Creating conversational AI agents using Gemini APIs
-
Integrating reasoning and personalization
-
Activity: Build a basic chatbot or question-answer agent
Learners start coding with Gemini APIs, getting hands-on experience in creating interactive agents that can chat, explain, and assist users.
Day 4: Connecting Agents with Real-World Data
-
Using Vertex AI to manage and deploy models
-
Integrating LangChain or similar frameworks for tool-use
-
Connecting AI agents to live data sources (like Google Sheets, APIs, or databases)
-
Understanding agent orchestration and workflow automation
-
Activity: Build an AI agent that performs a real task (e.g., retrieving data, summarizing information)
By this point, learners can make AI agents that go beyond chatting — they can perform actions and solve real-world problems.
Day 5: Final Project and Deployment
-
Review of all key concepts from the course
-
Best practices in AI ethics and responsible AI use
-
Final project: designing and deploying a functional AI agent
-
How to host your agent on a website or app
-
Completion ceremony and certification instructions
By the end of the course, learners have a working AI agent to showcase — a valuable addition to their portfolio or resume.

