A competitive online technical league by FODSE where participants register individually, get shortlisted, and compete through a team auction before taking on data-driven technical challenges as five-member squads.

A mentorship initiative by FODSE designed to guide participants through the hackathon journey, from ideation and problem understanding to solution development.

HeatCode 2026 is FODSE's Machine Learning competition that brings together students to solve real-world AI and ML challenges through the official Kaggle platform.

A hands-on opportunity where participants developed machine learning models focused on real-world issues aligned with the Sustainable Development Goals (SDGs). Attendees engaged with a provided dataset to predict outcomes related to critical topics such as climate action, health, and clean energy.

An extensive technical overview of the fundamental Azure services used in data engineering. Participants acquired hands-on experience developing, coordinating, and monitoring data pipelines, transforming data using Databricks and Spark, and doing sophisticated data analysis with Azure Synapse Analytics.

A collaborative environment where mentees learned about data science and machine learning from experienced seniors. Participants engaged in hands-on projects that allowed them to apply their knowledge to real-world scenarios, moving well beyond traditional tutorials.

A massive 24-hour inter-college Hackathon where teams pushed themselves to innovate new models and solutions for challenging problem statements.

A virtual mentorship initiative aimed at introducing beginners to Data Science and Python programming through interactive Google Meet sessions.

A dynamic data visualization challenge comprising two comprehensive rounds focusing strictly on data cleaning and visual storytelling.

A specialized web scraping event focused on automating data extraction from websites using code, allowing participants to explore real-world applications of data collection.