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University of Colorado Boulder

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 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.

Status: Sampling (Statistics)
Status: Applied Mathematics
IntermediateCourse29 hours

Featured reviews

KH

Reviewed Feb 27, 2024

The overall experience of the course was good but some of the questions were wacky at times

IL

Reviewed Sep 3, 2022

T​he instrustor, Dr. Jem, is really interesting. She made the hard part of the Statistics easy to understand!

DP

Reviewed Jan 27, 2024

Excellent. Challenging quizzes that really make you apply the points from the lectures. Very detailed course that has taken me to the next level of my understanding of statistical inference.

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