Student Success Prediction System

This project involved developing a predictive system to forecast student success based on historical academic data, attendance, and other relevant factors. By utilizing machine learning algorithms, the system analyzes student performance patterns to identify potential academic risks and predict outcomes such as graduation, course completion, and grades. The goal was to provide educational institutions with actionable insights to help guide students through their academic journeys, enabling early interventions for those at risk. The system’s predictive capabilities allow educators to make data-driven decisions, offer personalized support, and ultimately improve student retention and success rates.