online tutoring application helps students to search for best teacher and skill.The objective of tutorsync application is to develop a personalized tutoring recommendation system that employs advanced filtering technique collaborative filtering.To enhance the learning experience for students by providing tailored teacher and course recommendations for effective learning.Literature survey:Online education has a significant growth with the COVID-19 pandemic.Personalization in education is a factor for student engagement and success.Collaborative filtering techniques like User-Based Collaborative Filtering(UBCF) and Item-Based Collaborative Filtering(IBCF) have been applied in recommendation systems in various domains such as e-commerce and content streaming platforms.Their application in educational recommendation system is a evolving field.Current trends in online education are no longer sufficient for students who expect a customized content and support.Recommendation systems help them to find a best content and tutor for a specific topic based on their interest.The integration of data analytics and statistics into user progress and faculty performance by providing feedback for both students and educators to track and maintain the application.Business model:The business model of tutorsync can be achieved by creating a subscription-based platform.User can access basic features like creating profile and general recommendation for free.Premium subscription allow them to access advanced analytics,personalized tutor suggestion and more.The application for tutorsync are diverse and include schools,higher education,industry based training,skill training and also self-paced online course.The project aims to reshape the online education by delivering learning materials and matching student with best teacher of specific topic.