My Experience with the 5-Day AI Agents Course on Kaggle

Source: Dev.to

Overview

Over the past week I participated in Kaggle’s 5‑Day AI Agents Course, an intensive introduction to intelligent, autonomous agents. As someone passionate about AI but new to agent‑based systems, the course opened a completely new dimension of what AI can do. The lessons were short, hands‑on, and practical, allowing me to build and test real agents directly inside Kaggle notebooks with free GPUs and a collaborative environment.

Day‑by‑Day Learning Highlights

Day 1 – What AI Agents Are

Introduced the concept of agents as systems that can plan, decide, and act using tools—not just chatbots.

Day 2 – Building a Basic Agent

Created my first agent that could call a simple calculator tool, teaching the model to “think” step by step.

Day 3 – Multi‑step Reasoning

Developed an agent that breaks down a math word problem, selects appropriate tools, and solves it.

Day 4 – Retrieval‑Augmented Generation (RAG)

Learned how agents can pull relevant information from a knowledge base. Used this to build a simple FAQ bot.

Day 5 – Agent Memory

Implemented memory so the agent can recall context from earlier steps. Applied it to a mini project: a book‑recommendation assistant that remembers user preferences.

Final Project: Travel Assistant Agent

For the capstone I built a travel assistant that:

1. Asks the user about location and travel interests.
2. Fetches weather data.
3. Suggests destinations.
4. Generates a short itinerary using Python tools and a basic RAG setup.

The agent wasn’t perfect, but it demonstrated the practical potential of combining LangChain, Python, and external tools.

What I Learned

• LLMs alone are not agents; they need tools, memory, and structured prompts to become useful assistants.
• Prompt engineering is crucial—small changes can make huge differences.
• Combining LangChain + Python + external tools yields powerful results.
• Kaggle notebooks provide a beginner‑friendly environment with free compute, making experiments fast and easy.

Why This Course Matters

In the age of AI, agents represent the future of intelligent systems—whether as coding assistants, research helpers, or personalized bots. This course gave me foundational skills to move from using AI to building intelligent systems that can think, reason, and act.

Final Thoughts

I’m grateful to Kaggle and the #kagglexaiagentschallenge for this free, hands‑on learning opportunity. It sparked new ideas, boosted my confidence to build, and showed how accessible AI development has become.

If you’re even slightly curious about how AI can think, reason, and act, don’t miss this course!