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Statistical Estimation for Data Science and AI

This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good...

By Jem Corcoran on Coursera

About This Course

This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good estimators, method of moments estimation, maximum likelihood estimation, and methods of constructing confidence intervals that will extend to more general settings. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) and the Master of Science in Artificial Intelligence (MS-AI) degrees offered on the Coursera platform. These interdisciplinary degrees bring 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 CU degrees on Coursera are 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. Learn more about the MS-AI program at https://www.coursera.org/degrees/ms-artificial-intelligence-boulder Logo adapted from photo by Christopher Burns on Unsplash.

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Frequently Asked Questions

How much does Statistical Estimation for Data Science and AI cost?

Visit the Statistical Estimation for Data Science and AI course page for current pricing and available discounts.

Who teaches Statistical Estimation for Data Science and AI?

Statistical Estimation for Data Science and AI is taught by Jem Corcoran, University of Colorado Boulder.

What skill level is Statistical Estimation for Data Science and AI for?

This course is designed for all levels learners.

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Students0
Duration5 hours
LevelAll Levels
Languageen
PlatformCoursera