amos1575/DropAlert-Rwanda

# 🎓 DropAlert Rwanda: Predicting & Preventing Student Dropouts Through Data Intelligence ## 👩‍🎓 Student Information *Student Details:* - *Name:* [AMOS Nkurunziza] - *Student ID:* [26973] - *Course:* INSY 8413 | Introduction to Big Data Analytics - *Assistant Lecturer:* Eric Maniraguha - *Academic Year:* 2024–2025 (Semester III) - *Institution:* Faculty of Information Technology, AUCA - *Date:* Saturday, July 26, 2025 - *Tools Used:* Python (22 marks), Power BI (14 marks), Innovation (4 marks) ## 🎯 Project Introduction Education is Rwanda's cornerstone for national development and Vision 2050 achievement. However, student dropout remains a persistent challenge across Rwanda's educational landscape, particularly in lower secondary education where socio-economic barriers significantly impact student retention. *DropAlert Rwanda* represents an innovative, data-driven early warning system that leverages big data analytics and machine learning to: 🎯 *Primary Objectives:* - Analyze complex patterns of student dropout across Rwanda's provinces - Predict dropout risks with 99.2% accuracy using advanced ML algorithms - Visualize regional trends and disparities through interactive dashboards - Deliver actionable insights for education policymakers and stakeholders - Create targeted intervention strategies based on predictive analytics This comprehensive solution combines Python-based analytical tasks with Power BI visualization to transform raw education data into strategic intelligence that can save hundreds of students from dropping out of school. ### 🌍 Problem Statement "Can we predict which Rwandan students are at highest risk of dropping out using socio-economic and educational indicators, and create an actionable early warning system for stakeholders?" ### 📊 Sector Focus - *Primary Sector:* Education - *Target Level:* Lower Secondary Education - *Geographic Scope:* Rwanda (all provinces) - *Impact Goal:* Reduce dropout rates and improve educational equity ## 📊 …