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Statistical Inference for Estimation in Data Science に戻る

コロラド大学ボルダー校(University of Colorado Boulder) による Statistical Inference for Estimation in Data Science の受講者のレビューおよびフィードバック



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) 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 Christopher Burns on Unsplash....

Statistical Inference for Estimation in Data Science: 1 - 4 / 4 レビュー

by Daniel C


I feel like complaining it was very hard, but I can´t, it´s necessary. Jem Corcoran thruly wants you learn and share her experience with you. I recommend to go through the chapters again when finished, the concepts are not easy to digest at first.

by Óscar L R F


I​t was a tough one for me... completely worth it.

by Hidetake T


In depth understanding

by Parth K


Quite a few technical issues with labs and programming assignments which prevent you from progressing in the course.