Master’s in Data Science Courses & Curriculum | Northwestern SPS - Northwestern School of Professional Studies

Course Schedule, Part-time Online Program

Please note that course schedules may be amended due to low enrollment, faculty availability, and/or other factors.

Online Sync Sessions are an integral part of the online learning experience. Additional information about learning concepts and assignments may be discussed and sync sessions offer valuable opportunities for students to interact with their faculty and peers during the term. We encourage all students to attend live, but if they are unable to, sync sessions will be recorded and posted within Canvas to allow for an asynchronous model of success as well.

MSDS 410-DL : Supervised Learning Methods

Description

This course introduces traditional statistics and data modeling for supervised learning problems, as employed in observational and experimental research. With supervised learning there is a clear distinction between explanatory and response variables. The objective is to predict responses, whether they be quantitative as with multiple regression or categorical as with logistic regression and multinomial logit models. Students work on research and programming assignments, exploring data, identifying appropriate models, and validating models. They utilize techniques for observational and experimental research design, data visualization, variable transformation, model diagnostics, and model selection. 

This is a required course for the Analytics and Modeling specialization. 

Prerequisites: MSDS 400-DL Math for Modelers and MSDS 401-DL Applied Statistics with R.