CSCI 4900 Data Science Capstone
In this Capstone course for Data Science minors, students will apply their skills to real-world projects by working in teams on data science challenges provided by faculty members across the university. Projects may involve machine learning applications for STEM and social science research or data-driven insights for research in the humanities, education, nursing, or social work. Students will be assigned to teams according to their individual interests and major field of study, and they will meet regularly outside of class with their assigned faculty research mentor. The instructor and one or more graduate TAs will provide instruction and guidance during the weekly class meeting. The course will culminate in a final paper and a public presentation, either in a poster session or a series of talks, showcasing the students findings and analyses.
Course overview
- Department
- Computer Science
- School
- MCAS
- Credits
- 3
- Level
- Undergraduate
- Offered
- null
Catalog details
- Prerequisites
- CSCI2291
Requirements fulfilled
- Computer Science B.A.: CSCI 2000-level-or-higher elective (Current University Catalog; students should confirm their catalog year)
- Computer Science B.A.: CSCI 3000-level-or-higher elective (Current University Catalog; students should confirm their catalog year)
- Computer Science B.S.: CSCI 3000-level-or-higher elective (Current University Catalog; students should confirm their catalog year)
- Mathematics B.S.: Natural science, computer science, or economics corequisites (Current University Catalog; students should confirm their catalog year)
Official evaluation summary
Data freshness
Instructors
- Emily Prud'hommeaux
Sections
- Section 01