Statistical Modeling for Data Science Applications
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.
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- Level Professional
- المدة
- الطبع بواسطة University of Colorado Boulder
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Offered by
عن
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 https://www.coursera.org/degrees/master-of-science-data-science-boulder. Logo adapted from photo by Vincent Ledvina on UnsplashAuto Summary
"Statistical Modeling for Data Science Applications" is a professional course focusing on intermediate and advanced statistical modeling techniques crucial for data science. Taught by CU Boulder faculty, it covers linear regression, ANOVA, and generalized models using R. Ideal for IT and Computer Science professionals, it offers a pathway to CU Boulder’s MS-DS degree. Available on Coursera with Starter and Professional subscription options.
Brian Zaharatos