End-to-end ML pipeline for processing veterinary exam questions with interactive dashboards.
Developed for Ross University School of Veterinary Medicine, this analytics platform transforms how veterinary education programs assess and improve student outcomes. The system features an end-to-end ML pipeline that processes veterinary exam questions using Azure OpenAI GPT-4, automatically tagging questions by topic, difficulty, and learning objectives. An automated web scraping system built with Python and Selenium extracts data from the ExamSoft platform, while the interactive Dash/Plotly dashboard provides faculty with real-time insights into student performance, question effectiveness, and curriculum gaps. The platform implements strict FERPA compliance with role-based authentication and audit logging.