student-analytics

AI-powered student intelligence system for proactive intervention and analytics.

Machine learning and NLP-based prototype for clustering student behavioral and perceptual patterns in blended learning and generating personalized recommendation reports.

StudyMentor is an adaptive learning platform that helps students study smarter. It generates personalized quizzes based on each student's progress, keeps them motivated with a fun, gamified experience, and gives parents tools to stay involved and guide their child's learning journey.

Python-based learning analytics platform for student performance benchmarking, trend analysis, question-level diagnostics, weakness detection, and time-efficiency analysis.

Interactive Tableau dashboard analyzing employability trends, internships, projects, skills, and career readiness across 5,000 students.

A machine learning project that predicts student performance based on input features and generates personalized feedback using a smart dashboard.

Machine Learning model to predict MBA admission chances based on academic & profile features, with EDA, model comparison, and interactive insights.

Power BI business intelligence app analysing Udemy course completion rates, NPS performance, and learner engagement using DAX, KPI cards, scatter plots, and interactive dashboards to identify courses requiring improvement.

AI-powered academic guidance system that predicts student GPA and recommends personalized courses using collaborative filtering, Jaccard similarity, and PageRank algorithms. Built with Python ML backend, Node.js API, and web frontend for real-time academic planning assistance.

An end-to-end educational data analytics dashboard built for the Kayfa AI & Data Analytics Internship. Processes messy, multi-source dataset to surface actionable behavioral and academic insights via a MongoDB-backed Streamlit application.

A statistical programming exercise on student AI behaviour featuring machine learning with R and visualizations with a website via qmd.

AI platform for predicting university student dropout risk | LightGBM | SHAP | Streamlit | AUC 93.1%

AI-powered teaching preparation platform — multi-agent session planning, smart quizzes, analytics, and student learning tools built with FastAPI, React, and LangGraph.

Predicts undergraduate student graduation outcomes using Random Forest, XGBoost, and Logistic Regression with SHAP interpretability and Sankey diagrams to identify at-risk students early.

Student Outcomes Analysis using Python, Pandas, Matplotlib, and Seaborn. This project analyzes student performance data to identify trends in marks, attendance, and pass percentage. Developed as part of Data Analytics training.

AI-powered K-12 student analytics platform. Uses ML to predict behavior patterns, identify at-risk students early, and generate personalized learning recommendations. Built with Streamlit & scikit-learn.

End-to-End Education Analytics Platform for Student Performance, Engagement and Academic Intelligence using Python and Data Analytics.

AI-powered system for predicting student burnout, academic stress, and dropout risk using machine learning.

🚀 LifeTwin AI is an AI-powered Digital Twin platform that predicts student performance, stress, productivity, and placement using Machine Learning, interactive simulations, and personalized AI recommendations.

End-to-end student learning analytics project using Python, Pandas, SQL, SQLite, and Tableau to analyze student outcomes, engagement, assessment scores, and submission behavior.