International Journal of Scientific Research and Engineering Development

Personalized learning has emerged as a key approach in modern education systems to address individual student needs and learning styles. Traditional e-learning platforms often provide the same content to all learners, ignoring differences in pace, performance, and understanding. This paper proposes an AIPowered Personalized Learning Platform that uses machine learning algorithms to analyse student performance and recommend customized learning materials. The system integrates React.js for the frontend, FastAPI with Python for the backend, and PostgreSQL for data management. A recommendation engine analyzes quiz scores, learning behaviour, and topic engagement to dynamically adjust learning paths for each user. Experimental evaluation demonstrates improvements in learning efficiency, user engagement, and academic performance. The platform provides scalable and intelligent support for adaptive education

Shifa Bilal Tamboli, Simeen Phiroj Mulani, Arman Tajuddin Shiakh,"AI-Powered Personalized Learning Platform (Using Machine Learning and Web Technologies)" International Journal of Scientific Research and Engineering Development, V9(2): Page(2359-2362) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.