Applied Machine Learning in Education Research.

Catalog description

Semester course; 3 lecture hours (delivered online, face-to-face or hybrid). 3 credits. Prerequisite: EDUS 608 or equivalent or by permission of the instructor. An advanced-level course tailored for graduate students in education and related social science disciplines who are interested in integrating machine learning techniques in their research. Students will delve deep into core machine learning algorithms, data processing techniques and applications specific to education research challenges. The course will combine the technical rigor of machine learning with the nuances and needs specific to educational research. With a blend of individual mentorship, peer feedback and practical applications, students will be empowered to not just understand, but to apply these techniques to their research, producing work that stands up to academic scrutiny and has the potential for real-world impact.