Early-Warn AI: Student Performance Prediction System

Overview

Early-Warn AI is a full-stack, AI-driven analytical tool designed to identify "at-risk" students using historical academic and socio-economic data. The system aims for a minimum accuracy of 85% and provides actionable insights for educators.

Technical Stack

• Frontend: Next.js (React) with Tailwind CSS
• Backend: FastAPI (Python)
• AI/ML: Scikit-Learn (Random Forest / XGBoost)
• Database: PostgreSQL with SQLAlchemy ORM

Features

• Risk Dashboard: Identify at-risk students with visual indicators.
• Analytics: Performance trends and historical comparisons.
• Inference Engine: Real-time prediction with explainability.
• Simulation: "What-if" analysis tool.
• Automated Alerts: Early warning notifications.

Getting Started

Backend

1. Navigate to /backend
2. Install dependencies: pip install -r requirements.txt
3. Run the server: uvicorn main:app --reload

Frontend

1. Navigate to /frontend
2. Install dependencies: npm install
3. Run the dev server: npm run dev