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Opiniones y comentarios de aprendices correspondientes a Advanced Linear Models for Data Science 2: Statistical Linear Models por parte de Universidad Johns Hopkins

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12 reseña

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Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language. After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models....

Principales reseñas

SM
2 de abr. de 2020

This is a great course from Johns Hopkins University . By taking this course, I improved my Data Management, Statistical Programming, and Statistics skills.

ML
30 de ene. de 2017

Good course on applied linear statistical modeling.

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1 - 12 de 12 revisiones para Advanced Linear Models for Data Science 2: Statistical Linear Models

por Sehresh M

3 de abr. de 2020

This is a great course from Johns Hopkins University . By taking this course, I improved my Data Management, Statistical Programming, and Statistics skills.

por Peter

12 de oct. de 2019

It is a very good course for any statistics to learn and have a sweet tastes of math and its behind functionality on data.

por Mark L

31 de ene. de 2017

Good course on applied linear statistical modeling.

por Pawel P

18 de abr. de 2019

Very informative and interesting.

por Sergio G

23 de jul. de 2017

Very good... Thanks

por Wajdi A

6 de jun. de 2020

thanks u all

por SAYANTAN D

27 de jul. de 2020

Enjoyable

por RAMAKRISHNA R

30 de jun. de 2020

Very good

por Christian J H

12 de dic. de 2020

I love the deep dive into understanding the math, particularly the vector and matrix algebra, going on underneath the hood. However, I would've loved further examples that kept bringing things back around to how these things can be used in real world scenarios (i.e., biological and other scientific studies). There's a fine line between proofs providing valuable insight vs. proofs being purely academic, and this course may've flirted a bit too much with the latter to be as useful as it could've been.

por Sandeep J

7 de ago. de 2020

This course is very powerfull for statistical linear

por Ian K

22 de ago. de 2020

A very challenging and deeply insightful course.

por Mostofa K

29 de jul. de 2020

good