The course was great and really informative. Particularly, it was interesting to get to work with BAS and statr packages that were developed, essentially, by the instructors. I, however, think that from decision loss functions onward, the course suddenly became way more complex. The normal conjugate families were not discussed on the previous lab, and I believe deserve to be emphasized with an example before heading to regression and reference priors. However, the notes were quite helpful. All and all, it was a great course.

Its really hard for me to follow this specific course, its as if I am reading a summary of a novel rather than a novel, ideally this course should be broken into two courses and made into two five week courses. I may need to take additional courses or read some books to get a clear understanding.

In the previous three courses the open stats book helped a lot, however, the online content for this course is difficult to follow as well.

The course is well structured but the span of topics is large and the complexity great. Maybe an extended version with more explanations and demonstrations of the equations would be better for understanding the whole concept of bayesian statistics, specially inference.

Though this section in the specialization is a little more difficult than the other sections. The supplemental material provided is helpful in navigating through the course. I will continue to read through this material to further my understanding of the material.

The course is very interesting, but the jump from the previous course is too large. From calculating probabilities by hand and understanding the odds involved, to integrate distributions is too abrupt and not explained in detail.

Its a tough course however, I will just suggest to focus more on the practical side of things after doing all the theory. I really enjoyed course 4 where the professor used "R" to compare different models using the crime dataset.

I hope we can have access to the slides, and this can save attendees a lot of time, because I think after we finished watching the video we can skip relevant slides when we come across problems in doing exercise.

It was a good course, though I would include more coursework and exercises in R to assist with comprehending a difficult subject. Overall, good course for something that's difficult to teach.

The section about Beta-Binomial Conjugate is taught very fast and unless the student is quite familiar with Beta and Gamma distributions, it makes it very difficult to follow the course.

This is one of many good courses that one can get a glimpse of Bayesian statistics though it lacks of thorough explanation of mathematical background and reading materials of any kind.

Theis course is substantially more difficult than the three first ones, and the material is scarce. However, I must admit that this is one of the courses I have ever learnt the most

The instructors have great expertise, but this course is pretty difficult for a Bayesian newbie. Additional study guides would be helpful (especially week 4).

The course could have been more comprehensive and less verbose. It had so much content in a tiny course. Content should be less and more comprehensive.

A bit more depth in explaining conjugacy in priors and posteriors will be very helpful. A possible way would be to have more example illustrations.

Week 3 was too much information too soon, but week 4 was great again like the other courses in this specialisation. Learned so much, thanks!

Learnt a lot. Though the subject material was hard to grasp first hand, it is good that instructor was readily available to help us through.

An interesting and challenging course, would be better with more real examples and explanation as some of the material felt rushed

It's a good one, but not as previous courses. Week 3 isn't well explained as other weeks. Hope it can be further improved

The material is good. However, there is no support from the instructors to answer our questions in the discussion forum.

This course through the material too fast. The content should have been spread out over two courses in my opinion.

This is a very interesting topic. Lectures in weeks 3 and 4 could use some work.

Bayesian stats is a broad topic. Learners would benefit from more material.

Theorethical backdrop is a bit excessive on an R focused course

This course is challenging and well-presented!

Good content but sometimes it gets confusing.