Capstone for Artificial Intelligence and Machine Learning

Catalog description

The Capstone integrates prior coursework, research, colloquia, and professional experience, and provides the opportunity to synthesize theory with practice in an applied project, thesis, approved internship, or equivalent activity. Examples include developing an AI application or methodology, publishing a research paper at a previewed conference, or creating a startup company through YU's Innovation lab though students may propose other related projects based on their interests. The Capstone will include four components: a brief proposal and project schedule; the main deliverable (e.g. thesis, conference paper, working system with analysis/code/data); and a final presentation to the student and faculty body. Faculty will provide students with mentorship and feedback at each stage of the work.