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ジョンズ・ホプキンズ大学(Johns Hopkins University) による Regression Models の受講者のレビューおよびフィードバック

4.4
2,729件の評価
463件のレビュー

コースについて

Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing....

人気のレビュー

KA

Dec 17, 2017

Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.

BA

Feb 01, 2017

It really helped me to have a better understanding of these Regression Models. However, I've noticed that there is a video recording repeated: Week 3, Model Selection. Part 3 is included in Part 2.

フィルター:

Regression Models: 251 - 275 / 444 レビュー

by Naveen S

Sep 06, 2019

really it is very good

by Rizwan M

Sep 10, 2019

excellent courseware with assignments

by Muhammad Z H

Sep 15, 2019

learning alot

by Connor B

Sep 12, 2019

Learned a lot and enjoyed the course project. Would like to have two course projects because I gain the most out of them.

by Ravi K

Jun 12, 2019

This is really a nice training

by BOUZENNOUNE Z E

Sep 22, 2019

This was great. However, to follow it more precisely, you need the following: Read the book of linear regression from the same teacher. Usually a useful strategy would be to read each chapter first from the book, then watch the video associated to it, and finally do the swirl exercice.

You may need to follow the course notes of this class, they are published in github, and they can help a lot, especially for the quizzes.

by Сетдеков К Р

Sep 30, 2019

It was rather hard and time consuming, but I learned a lot about poisson and binomial regressions.

by Channaveer P

Oct 12, 2019

Amazing course... good learning experience. Very useful for my role in my Organization.

by Ashwin V

Oct 11, 2019

great course

by Dr. T A

Oct 12, 2019

A good review of regression that allows the student to apply practical implementations in R Studio

by Giovanni G

Oct 18, 2019

Very interesting

by Daniel J R

Dec 19, 2018

Quite practical. It does encourage one to follow-up with a more advanced course.

by David J B

Feb 19, 2019

Probably the most conceptually challenging and practically useful course in the JH data science certification series (so far... I have a few more courses to complete).

by Manny R

Mar 22, 2019

Really Fun Course. There is a lot to learn in this topic and this could be studied for a lifetime. I feel like I could apply this to discover solutions for issues at work.

by Dora M

Mar 30, 2019

Good class.

by John D M

Apr 10, 2019

Overall an excellent course, but there were some issues with the wrong function being specified in one quiz (Q3q6) and the wrong answer in another. Apparently it has been that way for years, according to the forum. The quality of the lectures was very high and the information interesting, so compliments to Dr. Brian Caffo on that. However, the estimated time for completion of each week is ridiculously short compared to reality. Five hours? For me it was more like 20 hours, and more if I did all the Swirl exercises. Such low-balling on the time estimates is typical of the Data Science stream. The final project is given as 2 hours but it was closer to 15 for me. i wish Coursera would go back to the stream model where you could bump yourself to the next intake. That is much less stressful for busy working people like me.

by Paul R

Mar 13, 2019

Relatively, this is one of the best courses and lecturers of the specialization, Brian delivers clear, thorough and well-paced lectures. These lectures on statistics, regression and machine learning are where the rubber hits the road after a lot of prep work to learn R and principles/tools of data science taught in earlier classes.

by Alzum S M

Jan 08, 2019

Very much thank you for teaching me such an awesome course

by Nathalie D

Mar 11, 2019

Great course, but please check those subtitles that are occasionally completely off!

by Roopak M

Sep 10, 2018

Nice course that helps make your foundations in regression modelling strong. The complexity of the course project can be increased to a more difficult level.

by Pooia L

Sep 13, 2018

This is a very nice course provided you study a lot for it

by Daniiar B

Sep 27, 2018

Very hard to understand

by Nevon L D

Sep 27, 2018

Builds Heavil

by Jamison R C

Aug 28, 2018

Excellent course, though I recommend you supplement applied practice by using the principal instructor, Dr. Brian Caffo's book, to answer practice questions if you want to retain these content-packed lessons. Better yet, begin each week by looking at the quiz and printing it out. As you view the relevant content, answer the related questions (which are generally presented in order of delivery).

by Yusuf E

Aug 15, 2018

I am almost certain that regression models have more relavance in an academic setting than industry. But this doesn't affect really how I graded this course. I wish Brian skipped over the first week which entirely deals with regression to the mean. Weeks 2 and 3 were very good and detailed.

I am not sure if logistic classifier is mentioned in the next course but it would probably be best if this part would be included in the ML course. Other than that great course and very challenging quizzes.