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Data Science

Course Descriptions and Schedule

MSDS 454-DL : Advanced Modeling Techniques


Drawing upon previous course work in data science, this course build on earlier courses in analytics and modeling, providing an advanced review of traditional statistics and machine learning. It explores computer-intensive methods for parameter and error estimation, model selection, and model validation. Example topics include ordinary least squares regression, logistic regression, multinomial logistic regression, classification and regression trees, neural networks, support vector machines, naïve Bayes methods, principal components analysis, cluster analysis, and regularization techniques. Students work on individual and team assignments using open-source programming tools.

Recommended prior course: 411-DL Generalized Linear Models.

Prerequisites: MSDS 411-DL Generalized Linear Models and MSDS 422-DL Practical Machine Learning.

Winter 2019
Start/End DatesDay(s)TimeBuildingSection
01/07/19 - 03/25/19Optional Sync Tu
7 – 9:30 p.m. 55
InstructorCourse FormatStatusCAESAR Course ID
Chaturvedi, Anil

Winter 2019
Start/End DatesDay(s)TimeBuildingSection
01/07/19 - 03/25/19Optional Sync Sa
9 – 11:30 a.m. 56
InstructorCourse FormatStatusCAESAR Course ID
Bhatti, Chad
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