Poor explanations throughout. You'd be best served by learning the topics from a secondary source and then coming back to decipher the lectures and videos. Needs many more examples, this course is instead full of an equation, a simulation, and a hearty "good luck!"

I love the content but:

imprecision (a lot),

lack of explanation

...

for one of the most difficult subject in the specialization.

Last commit/update for the video from the teacher 1/2 year ago: are the materials update?

I would like to propose that instead of putting the optional reading materials at the back, it should be put up front and mandatory. Else we can't follow the videos

Should cover a lot of dfificuties when the model assumptions are violated and should be for a longer time or having a second course about this theme.

Needs more practical examples. Could be rerecorded. I love mathematical theory but past week 2 it is really too theoretical, in my opinion.

way to much emphasis on non-data science. This one course covers more information that the rest of the courses combined..

Very difficult. Needs homework problems guided by videos like Statistical Inference coarse to make easier.

Would love to "Unenroll" but can't.

Can someone please take this course off my dashboard?

To fast pace and missing lot of content to make this lesson enjoyable!!!

The course was nowhere near of interesting. It was arduous and boring.

Difficult, fast peaced and not well explained. Requires a lot of work.

The instructor is not good and doesn't explain things clearly.

Some topics that are important, are obviated

Coursera keeps changing my rating. Not cool.

not effective for new learnners

The course is essentially just a review of formulas with very little intuition explained to the beginner. It was necessary to use a collection of outside material from other courses and readings to learn the concepts. This course needs to be completely redone with a focus on developing a student's intuition for the material and then support this intuition with basic examples that build as the course progresses. A fundamental demonstration of how to use R to work through regression models (starting from square one) should be added so that this becomes a self-contained course. As it currently stands it is a collection of poorly integrated slides and concepts that serve to confuse the student more than educate. Other classes teach this material infinitely better.

I was really disappointed with this course. I took the other courses from Brian Caffo and truly enjoyed them. For the previous courses, I've always used the books and they helped me tremendously to be able to comprehend the material. There is a book for Regression Models but but it's a real mess. It feels like a draft that no one cared to take a second look. There is a bunch of wrong code and typos. The explanation doesn't go as far as it should. I had to resort to many different sources just to be able to get by the course. I hope the instructors review this course soon because it does not have the same quality as others. If they don't review it, don't bother paying for it. Try learning Regression Models elsewhere.

I have wasted my money by enrolling in this course. After every swirl programming, there is some issue and I have to restart the Lab session again. I have completed 88% of swirl Lesson 9- Functions, three times now, sometimes I get the output, sometimes error, with the same code. In my R studio, output is coming, but online, it's giving output, but then ">" symbol comes and then nothing. I have been struggling with this course. Pathetic one!!! I wont be able to finish this course like this, not even in a year. I want a refund!!!

This is, by far, the worse course of the whole specialization. The instructor has a talent to make this whole topic way more complicated than it is. I ended up auditing the Duke University course on the same subject to understand the concepts, as well as watching many youtube videos, which allowed me to properly do the course project (which is the only good thing about this course: applying what you've learned). I cannot recommend this course to anyone if it's not as part of the specialization.

I tried to just deal with this course and the previous one (statistical inference) because I have been doing this for a lot of years. It's because of that, I passed this class. Those with no experience will find it hard to understand what is being taught without some additional help. Additionally, nothing that is taught is focused on in the quizzes or the final project, just some pieces, so why use those as grading methods?

The most worthless waste of my time this year. I learned more in an hour of browsing external sources than I did from the entirety of the course material, which was poorly structured and extremely dull. Were I not so heavily invested in this specialisation already, I would have cancelled my subscription over it.

Very little depth. I don't recommend this if you don't already have background in statistics or R. I really didn't learn anything. I mostly just gamed the quizzes and projects.

Terrible. If you want to learn about regression, even in R, go elsewhere. This course damages the brands of Johns Hopkins and Coursera...anybody heard of quality control?

Terrible. Lectures are useless and Questions are very hard. A lot of studying then comes from searching the internet, which nullifies the need of taking the course.

This is the whole course that kind of discouraged me persuing data science field... i wish i wish i wish there was different instructor