Datathon

“Datathon – Compete. Compute. Conquer”. The goal of this competition is to equip participants with the ability to design, implement, and evaluate data-driven predictive models using real-world datasets. The Datathon is carefully structured to mirror the end-to-end workflow of real-world data science projects, providing participants with practical, industry-relevant experience.  The challenge begins with an aptitude evaluation to assess participants’ analytical thinking and problem-solving skills. This is followed by problem framing, where teams interpret the given problem statement and define appropriate objectives. Participants then proceed to data cleaning and preprocessing, handling missing values, noise, and inconsistencies to prepare quality datasets for analysis.  Next, participants engage in model development, applying suitable statistical, machine learning, or predictive techniques to extract insights and build effective models. The final phase focuses on performance assessment, where models are evaluated using appropriate metrics, and results are interpreted to derive meaningful, data-driven conclusions.  Through this structured approach, the Datathon aims to bridge the gap between theoretical learning and practical application, strengthening participants’ capabilities in analytical reasoning, technical implementation, and result evaluation. Ultimately, the competition prepares students to confidently tackle real-world data science challenges by simulating professional workflows in a competitive and collaborative environment.