A Portfolio of
Data-Driven Solutions

University Online Learning Platform data analysis and forecasting

I developed a data science project to forecast student interaction and engagement with an online learning platform and predict their final academic status. Using a dataset that includes student demographics, engagement metrics, and academic performance, I built predictive models to analyze these factors. Streamlit was employed to create an interactive web application, allowing users to visualize and explore the predictions and insights. This tool helps educators and administrators make data-driven decisions to improve educational outcomes and support student success.