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MATH 650: Statistical Methods for Data Science

Credit: Trifonov Evgeniy Getty Images

MATH 650: This is a course on statistical methods for data science with an emphasis on statistical learning. It provides a set of tools for modeling and understanding big and complex data. This course concentrates on applications and practical execution of the methods rather than on mathematical details. Areas discussed include various regression models, classification methods, resampling, non-linear techniques, tree-based analysis, support vector machines, and unsupervised learning. The programming language R will be introduced, and used throughout the course.

LinkedIn Learning Resources

To check out all Linkedin Learning has to offer, click here! Or, visit some of the courses related to data science, programming in R, and Statistics below. 

R Programming in Data Science: Setup and Start 1 hour 42 minutes

Learning R 2 hours 51 minutes

Data Science Foundations: Fundamentals 3 hours 41 minutes

Statistics Foundations: 3 1 hour 41 minutes

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