Chevron Left
Voltar para Advanced Linear Models for Data Science 1: Least Squares

Comentários e feedback de alunos de Advanced Linear Models for Data Science 1: Least Squares da instituição Universidade Johns Hopkins

166 classificações

Sobre o curso

Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. 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....

Melhores avaliações


16 de mai de 2020

I really enjoyed the course. It was well explained and the quizzes at regular intervals were helpful. It would be great if there were some practice exercises though...


7 de jun de 2016

We need more advanced, theoretical courses on Coursera, like this one, in order to deeply understand the more general courses like Regression Models and Linear Models.

Filtrar por:

26 — 42 de 42 Avaliações para o Advanced Linear Models for Data Science 1: Least Squares

por Ryan G

11 de jun de 2019

The coding videos with R are outdated. But this is to be expected since R is open-source and changing rapidly. The code videos should be updated frequently to coincide with the latest release of R and R Studio. I like that code example content is placed into separate videos. The videos are very clear and easy to see. If lecture segments are re-worked, I'd suggest writing in a single column, and keeping the new content always in the center of the screen. There is some inconsistencies in the notation, and some content is repeated too often. But it's not like salt: too much isn't nearly as bad as not enough.

por Christoph L

3 de set de 2020

A good course that has some insights (especially for regression) but that feels towards the end very cut together from other existing materials. Thus, there are some jumps in the topics and some repetitions of subjects. It feels like some aspects such as the partitioning of variability (week 6) could have been explained more easily.

por Mohit Y

6 de jan de 2022

T​he covers several topics with links to additional videoes which are valuable for understanding the derivation and concepts, the quizes are well constructed for evaluating conceptual understanding. Overall the course is quiete good, there could have been a few more applied examples for applying the learnings in practice.

por Melcior R

7 de fev de 2021

I would appreciate more practical exercises with R. But Prof. Caffo was very good at explaining concepts and give the nuisances behind a model, I do really appreciate his style of putting things together. Highly recommend this course and the professor.

por Xinpeng H

7 de mai de 2017

I enjoyed the math and it helped me to review my linear algebra and got new intuitions on linear regression. But there are a few typos that need to be fixed. It would be better to open a forum and let student discuss with each other.

por Jean p A

9 de set de 2020

This is an excellent course that enabled me to understand how multiple regression in linear models works behind the hood. The practical examples shown by the professor were very helpful. Thank you

por Jens R

7 de nov de 2017

Great, detailed walk-through of least squares. Linear Algebra is a must for this course. To follow the last part requires knowledge of matrix (eigen?)decomposition, which derailed me somewhat.

por Gustavo F

10 de set de 2019

El curso es bueno, sin embargo me gustaría que pusieran notas sobre las ecuaciones o un pequeño resumen, ya que yo al menos no tengo dinero para comprar los materiales.

por Jerome M

9 de mai de 2017

Good course. Quite hard. Linear algebra should be your second language as it is assumed to be mastered. Exams should include some personal work.

por Zhe R

10 de jan de 2022

P​retty challenging since I haven't got close to linear algebra for awhile. Need at least intermediate math background in this class.

por Richard M

23 de fev de 2017

Hard Topic, You must take all the basics in multivariate statistical analysis first.

por Chris L

30 de abr de 2020

The course is interesting; but is more theoretical in nature than applied.

por Zitong W

15 de fev de 2019

Not an advanced level course.

por CJ

22 de jul de 2020

Nice Course.

por Alejandro C

28 de jul de 2017

Great Course

por Joseph I

28 de abr de 2021

The material was incredibly interesting but especially for weeks 4-6 the lectures seemed to have been pieces of much broader lectures and therefore were difficult to follow. I spent more time researching the material than I did on the course.

por Stan M

15 de fev de 2021