I led the development of a personalized AI-driven learning platform for 20,000+ students. The goal was to enhance student engagement and retention by leveraging machine learning to track real-time student journeys and provide personalized recommendations for their learning paths.

The project involved architecting an MLOps pipeline on Microsoft Azure, integrating data from 15 different sources to enable real-time tracking of student progress. By analyzing this data, we were able to create a system that delivered tailored learning experiences, improving student engagement by 35% and increasing retention rates by 20%.

In addition, I developed over 20 interactive dashboards and reports using Power BI to automate 40% of manual analysis tasks, making data-driven decision-making faster and more efficient. This project required deep collaboration across teams to ensure the platform was scalable, user-friendly, and met the specific needs of higher education institutions.

This work demonstrates my ability to lead and deliver complex AI and data science projects that have a measurable impact on user engagement and operational efficiency.