RUNetworking: Unified Course Planning and Student Networking Platform

RUNetworking demonstration

Problem Statement

Currently, the resources for finding course information and planning schedules at Rutgers are scattered across the web and uncoordinated, making it complicated and inconvenient for students to find the information they need to register for classes. Additionally, students want to meet other people who share the same interests, but huge lectures and small recitations make it hard to meet most of the people in their classes.

Proposed Solution

RUNetworking offers a comprehensive platform that:

• Consolidates course information from various Rutgers websites into a unified, searchable database.
• Implements an AI-powered scheduling assistant using the OpenAI API with the latest state-of-the-art LLMs to answer detailed questions and suggest courses based on major requirements, career goals, and personal interests.
• Creates student profiles that facilitate both course planning and peer connections, enabling students to discover and connect with classmates who share similar schedules, interests, or career aspirations.

Target Audience

University students who need to navigate course selection each semester and seek meaningful connections with peers sharing similar academic paths. Particularly useful for new and transfer students.

Impact and Value Proposition

The platform will streamline the course selection process while fostering a more connected campus community by:

• Consolidating information from multiple sources and using an LLM to make the information dramatically more accessible and useful to students.
• Facilitating meaningful student connections based on shared academic interests.

Innovation and Feasibility

Technical implementation utilizes:

• Data Integration: Official Rutgers schedule of classes API and Python Selenium for web scraping additional course information.
• AI-Powered Assistance: OpenAI API with the latest state-of-the-art LLMs and Retrieval Augmented Generation (RAG) for affordable and intelligent course recommendations and access to up-to-date information.
• Scalability & Performance: Built with Next.js, Node.js, SQL, Supabase, and AWS to ensure cost-effectiveness and scalability.

Conclusion

RUNetworking aims to streamline the course selection experience at Rutgers while building stronger student communities. Our application will transform the way students interact with academic information and with each other.