Problem Statement

Access to personalized and quality education remains a challenge, particularly in remote areas. Students often lack the resources and individualized support needed to effectively grasp complex subjects, leading to disparities in learning outcomes.

Solution

The solution is "SmartTutors," an advanced interactive tutoring system that leverages Retrieval Augmented Generation (RAG) to provide personalized study materials, answer intricate questions, and adapt to each student’s unique learning style. This system enhances learning outcomes and expands access to quality education, especially for underserved communities.

Technical Aspect

SmartTutors utilizes RAG pipelines and fine-tuned Large Language Models (LLMs) to generate accurate responses and customized study content. The system integrates advanced Prompt Engineering, effective deployment strategies, and a user-friendly front-end interface to optimize interaction and accessibility for students.

My Contribution

I was responsible for the data optimization part, ensuring efficient retrieval and processing of educational content. My work involved refining data structures, optimizing query response times, and enhancing the accuracy and personalization of generated study materials, contributing to a seamless and effective learning experience for students.