Data Science Pathways in Education
The educational goal of TRIPODS@Duke is to develop and implement a Data Science Pathway that targets the entire “data to knowledge to action” pipeline to prepare undergraduates, graduate students, and postdoc trainees in cutting-edge data science research, being able to wrangle and analyze data in a responsible and ethical manner, and being able to work effectively in interdisciplinary teams.
Undergraduate
View our interactive Data Science interdisciplinary course map.
Departmental Pathways
- Computer Science
- Degree Programs
- Interdepartmental Majors (also detailed below)
- Electrical & Computer Engineering
- Degree Programs
- Concentration in Machine Learning (open only to ECE majors, Complete five courses—Earn a notation on your Duke transcript)
- Minor in Machine Learning and AI (open to both Pratt and Trinity undergraduates)
- Mathematics
- Statistical Science
- Degree Programs
- Interdepartmental Majors (IDMs) (also detailed below)
Interdepartmental Majors (IDMs) combine two academic disciplines in Trinity College, drawing 7 courses from each to create a major.
- Data Science – Computer Science and Statistics
- Data Science – Computer Science and Math
Research Opportunities
- Data+
- Duke Opportunities in Mathematics (DOmath)
- Code+
- Program for Research for Undergraduates (PRUV)
Activities
Reading Groups
Theoretical Aspects of Deep Learning
Fall 2022 date and time to be announced – via Zoom
Contact Jianfeng Lu to join: jianfeng@math.duke.edu
The reading group meets and discusses recent works in mathematical and theoretical analysis of deep learning models and algorithms.