Building a practical health agent my learning experience with "Google" and "Kaggle".

My Learning Experience in the AI Agents Intensive Program

This post shares my structured learning experience from the AI Agents Intensive Program by Google and Kaggle. It highlights the key concepts I learned, my project idea, and practical suggestions for improving future editions of the course.

Key Learnings from the Program

The AI Agents Intensive gave me a clear and practical understanding of how modern AI systems work. I learned how:

Agents make decisions using reasoning

Tools enable agents to perform real actions

Workflows guide step-by-step task execution

Memory helps agents respond intelligently

Prompts shape the system's behavior

These concepts helped me understand how real, functional AI assistants are built.

My Project Idea: Building a Health Agent

Using the concepts from the course, I planned to design a Health Agent capable of:

Providing basic wellness and health guidance

Supporting healthy habits

Offering simple first-aid information

Giving reminders for hydration, sleep, sunlight exposure, etc.

Although I could not submit the capstone project due to unclear submission communication, the project idea remains valuable, and I am continuing to work on it independently.

What the Program Did Well

The course was strong in several areas:

Clear explanations of concepts

Useful demonstrations of tools

Encouraging and active community support

Easy-to-follow pace for beginners and intermediate learners

Overall, the program successfully made advanced AI concepts easy to understand.

Areas That Could Be Improved

Every learning program can grow further. Here are a few areas where improvements can make it even better:

1. More Hands-On Tool Practice

Tools were introduced well, but additional guided exercises would make the learning stronger.

1. Clearer Capstone Submission Process

Many participants, including myself, did not receive a clear submission path. A visible “Submit Project” button would help.

1. A Complete End-to-End Example Agent

A full production-level example would help learners understand how all components connect.

1. Better Mobile Experience

Some pages and UI elements did not load properly on mobile devices.

These improvements would make the program more seamless and accessible.

Final Reflection

This course strengthened my confidence in AI development.
It showed me that anyone—with the right guidance and consistency—can create meaningful AI systems.

I will continue developing my Health Agent into a reliable, practical companion that helps people improve their daily well-being.
Thanks to all guy's.