AI-driven Student Success Prediction Platform

In the ever-evolving landscape of Higher Education, institutions are increasingly tasked with improving student retention and success rates. Our company seeks to address this challenge with the development of a sophisticated AI-driven Student Success Prediction Platform. By harnessing the power of advanced technologies such as LLMs, Computer Vision, and Predictive Analytics, the platform will analyze a multitude of data sources including academic records, attendance, participation, and even facial sentiment analysis from class recordings. Our goal is to provide educators and administrators with precise predictions and insights into student performance trends. The project will integrate key technologies such as the OpenAI API for NLP tasks, TensorFlow and PyTorch for model development, and Pinecone for vector database management. The platform will also utilize Langchain to streamline communication between components and Hugging Face for pre-trained models, with YOLO assisting in processing visual data. Upon completion, the platform will enable institutions to proactively identify at-risk students and tailor interventions, ultimately enhancing student outcomes and institutional reputation.