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Data Science
DAS-211 Machine Learning for Data Scientists
This course covers the fundamentals of machine learning for data scientists. Students will learn about training data, and how to use a set of data to discover potentially predictive relationships. Topics covered include supervised and unsupervised machine learning, generalized linear models including multivariate linear regression and binary logistic regression, automatic feature selection, bootstrapping, simple reinforcement learning, and decision trees. Applications will be emphasized throughout. A programming language will be used.
DAS 170 and MAT 150; or permission of the instructor.
Program: Data Science
Credit: 3
DAS-110
Introduction to Data…
This course builds on the foundation established in…
Credits 3
DAS-105
This course is a hands-on, beginner-friendly course designed…
DAS-595G
Special Topics
Special topics courses address subject matter or content…
DAS-533G
Advanced Geographical Information…
The course introduces students to ArcGIS Pro mapping…
DAS-532G
Fundamentals of Geographic…
The course introduces students to ArcGIS Online, an…
DAS-595U