Dive into my portfolio to explore a groundbreaking thesis titled "Prediction of Varendra University Students' Performance Using Machine Learning Techniques." In this project, I unravel the intersection of technology and education, employing cutting-edge machine learning methods to predict and enhance student performance at Varendra University. From tracing the historical evolution of predictive analytics to evaluating diverse methods, including statistical models and data mining techniques, my work bridges the gap between data science and pedagogy.
The portfolio provides a comprehensive overview of the core data used for performance prediction, emphasizing the pivotal role of variables like student records and demographics. Discover the wide-ranging applications of performance prediction, from early warning systems to personalized learning and program evaluation. Ethical considerations, such as data privacy and algorithmic bias, are also explored, showcasing a commitment to responsible predictive modeling in education.
As you navigate through my portfolio, gain insights into emerging trends in educational performance prediction, incorporating big data, artificial intelligence, and predictive analytics. The thesis not only provides a glimpse into the future of personalized learning but also outlines potential directions for future research, laying the foundation for a transformative approach to enhancing student performance at Varendra University. Join me on this journey at the forefront of data-driven decision-making in higher education.