CourseCurriculum
Eligibility
GradeForecaster
Login page
Student_page
MentorshipLog
ExecutiveAnalysis
CareerReadiness
FacultyDashboard

Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for AI-Powered Academic Performance Analytics

Introducing my project: AI-Powered Academic Performance Analytics and Personalized Learning Recommendation System for Higher Education Institutions.

This project aims to help students and faculty gain meaningful insights into academic performance using data analytics and machine learning.

Key Features:

Student academic performance dashboard
Subject-wise and topic-wise performance analysis
Weak subject and topic identification
Academic risk prediction using Machine Learning
Explainable risk analysis
Personalized learning recommendations
Personalized learning paths and study plans
Learning progress tracking
Before-and-after performance improvement analysis
Faculty dashboard and class-level analytics
What-if score simulator

Technology Stack:

Frontend: React.js, Vite, Tailwind CSS, Recharts
Backend: Python, Flask
Database: MongoDB
Machine Learning: Python, Pandas, NumPy, Scikit-learn

The primary objective is to go beyond traditional marks-management systems by identifying learning gaps, predicting potential academic risks, and recommending suitable learning resources for individual students.

This project explores how AI and machine learning can support personalized learning and data-driven academic decision-making in higher education.