This is a submission for the Google AI Agents Writing Challenge: Learning Reflections
Being a tech-enthusiast, eager to learn about the emerging buzzword technology - How to build AI Agents? Curious to learn, build and grow - there I got the perfect for beginners 5 Day --> AI Agents Intensive Course with Google and Kaggle.
Overview
Day 1:Introduction to Agents
Day 2:Agent Tools & Interoperability with Model Context Protocol (MCP)
Day 3:Context Engineering: Sessions & Memory
Day 4:Agent Quality
Day 5:Prototype to Production
Sneak peek
Learning Reflections
I learnt to built AI agents using Google's Agent Development kit. Not only an agent but also multi-agent systems. This course was a power pack bagged with daily assignments including summary podcasts, whitepapers, live streams and code labs.
Through this course, I explored new ways to add tools to extend what agents can do, best practices for tools, including using MCP and long-running operations, how to build stateful agents and perform context engineering, how to use memory with agent, how to implement observability, evaluate agents and how to use Agent2Agent (A2A) Protocol to have agents interact with each other.
The last part of the course was the production and deployment. I learnt about the deployment of agents to Agent engine on Google Cloud.
Being a beginner, Google and Kaggle helped me a lot to learn about AI Agents effectively.
Capstone Project
Although it was an optional part of the course, I enrolled to build a capstone project to showcase my learning experience through a project. Building a project based on the skills you have learnt gives an edge!
I build an AI agent for sustainability highlighting the concept of Agentic AI for smart cities. Its a small prototype build by me based on my 5 days learning experience. I am excited to scale up my project and learn ahead about AI agents.
Don't forget to visit --> (https://www.kaggle.com/code/rsy124/sustainability-ai-agent[])
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