This mini hackathon is a hands-on, problem-solving session designed to help participants apply their Machine Learning skills in a practical setting. The event focuses on turning ideas into working solutions by combining ML concepts with real-world datasets and structured project building.

The hackathon is conducted in two phases. In the first phase, participants work with four curated datasets and guided project ideas to understand problem statements and plan solutions. In the second phase, participants move into Firebase Studio–based project building, where they develop, organize, and prepare their ML projects in a hackathon-style environment. This event helps participants gain confidence in building, structuring, and presenting ML-based projects.