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University of Colorado Boulder

Statistical Modeling for Data Science Applications

University of Colorado Boulder via Coursera Specialization


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Statistical modeling lies at the heart of data science. Well crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In this three credit sequence, learners will add some intermediate and advanced statistical modeling techniques to their data science toolkit. In particular, learners will become proficient in the theory and application of linear regression analysis; ANOVA and experimental design; and generalized linear and additive models. Emphasis will be placed on analyzing real data using the R programming language. This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at Logo adapted from photo by Vincent Ledvina on Unsplash


Course 1: Modern Regression Analysis in R
- Offered by University of Colorado Boulder. This course will provide a set of foundational statistical modeling tools for data science. In ... Enroll for free.

Course 2: ANOVA and Experimental Design
- Offered by University of Colorado Boulder. This second course in statistical modeling will introduce students to the study of the analysis ... Enroll for free.

Course 3: Generalized Linear Models and Nonparametric Regression
- Offered by University of Colorado Boulder. In the final course of the statistical modeling for data science program, learners will study a ... Enroll for free.


Taught by

Brian Zaharatos


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