Regression and Classification
Statistical Learning for Data Science,
Introduction to Statistical Learning will explore concepts in statistical modeling, such as when to use certain models, how to tune those models, and if other options will provide certain trade-offs. We will cover Regression, Classification, Trees, Resampling, Unsupervised techniques, and much more! This course 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.
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Rating | Not enough ratings |
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Length | 7 weeks |
Effort | 6 weeks of study, 4-10 hours per week |
Starts | Jun 26 (44 weeks ago) |
Cost | $99 |
From | University of Colorado Boulder via Coursera |
Instructor | James Bird |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Mathematics |
Tags | Data Science Data Analysis Math And Logic Probability And Statistics |
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Rating | Not enough ratings |
---|---|
Length | 7 weeks |
Effort | 6 weeks of study, 4-10 hours per week |
Starts | Jun 26 (44 weeks ago) |
Cost | $99 |
From | University of Colorado Boulder via Coursera |
Instructor | James Bird |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Mathematics |
Tags | Data Science Data Analysis Math And Logic Probability And Statistics |
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