Data Science

This course will emphasize problem solving in business contexts using data analytics. The course focuses on predictive modeling, data mining, and decision support systems. It combines theoretical development of analytic tools with practical, hands-on experience using programming software to examine

This course will emphasize problem solving in business contexts using data analytics. The course focuses on predictive modeling, data mining, and decision support systems. It combines theoretical development of analytic tools with practical, hands-on experience using programming software to examine real data and case studies.

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.

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.

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.