Data Science

Courses

DS 388: Methods for Research and Dissemination

Credits 3

This course provides an introduction to the process of developing and writing a research proposal. In the course, students will focus primarily on the learning of how to select an advanced topic, write annotated bibliography, identify appropriate data sets and sources, review related literature, and finally write a proposal. The course emphasizes the process of designing and writing research proposals.

DS 401: Statistical Modeling for Data Science

Credits 3

Topics include the mathematics of linear regression, multilinear regression, logistic regression, time series and PCA and their applications using the Python programming language. Students will be applying these concepts in the context of projects.

DS 481: Internship

Credits 3

An internship or practicum organized by the student in consultation with the adviser. Credits for the experience must be negotiated between the adviser and the on-site supervisor. The experience involves one of the following: (a) teaching or tutoring a second language, (b) a special research project or (c) interpreting / translation. Depending on the experience, students enhance their communicative skills, develop a critical understanding of linguistic and cultural differences, connect to other disciplines through languages, come to a deeper understanding of the role of translation in cross-cultural communication, and/or reflect on career and life goals.

DS 488: Senior Capstone

Credits 3

Individual and collective investigations into topics of common data science interest not covered in the department's regular course offerings. A significant part of this course is students' reading new data science materials and presenting it to one another.