Sloan Data Science Faculty Fellows Program

The Spelman/Michigan State University (MSU) Data Science Collaboration invites three (3) faculty to participate in the AY 2022/2023 Sloan Data Science Faculty Fellows Program. As a Sloan Data Science Faculty Fellow, you will receive training in data science technologies that you may incorporate into your research and teaching. Faculty fellows will complete two courses in data science.
No prior knowledge or experience in programming or data science is assumed. The courses will include skills in programming (Python) and modern methods in machine learning.
Sloan DS Faculty fellows will receive two weeks of summer salary, and one additional week of salary and one course release during the academic year. The course release must be approved by your department chair.
Data Science Coursework
The data science coursework will begin with a one-week intensive in Summer 2023. The coursework will be facilitated by a faculty member from MSU. They will meet with faculty in person at Spelman during the one-week intensive. Periodic virtual meetings will continue through the academic year. Faculty will be provided online materials to help their progression through the courses.
The courses are modeled after CMSE 801: Introduction to Computational Modeling and CMSE 840: Applied Machine Learning. CMSE 801 will conclude in December and will be followed by CMSE 840 in the Spring Semester. A description of the courses is provided below.
CMSE 801: Introduction to Computational Modeling – This course uses a variety of application examples, numerical methods, data visualization, and algorithmic thinking and model building. The course will include programming.
CMSE 840: Applied Machine Learning – This course uses a project-based approach that covers the techniques of modern machine learning.
Other Activities
- Participate in the Joint Spelman/MSU Data Science Seminar
- Collaborate, where there are areas of mutual research interest, with faculty at MSU on joint research projects
Deliverables
Sloan Data Science Faculty Fellows are expected to contribute to or design a course for the Spelman Data Science Minor (under review), develop data science content/modules for their courses, or work with Spelman student on undergraduate research projects in data science.
2022-2023 Faculty Fellows
- Michael Burns-Kaurin, Ph.D. – Associate Professor, Department of Physics
- Kiandra Johnson Headspeth – Senior Instructor, Department of Mathematics
- Unislawa Williams, Ph.D. – Associate Professor, Department of Political Science