Very Good

helpful

great

good

Awsome course overall. I took one star away for the capstone project's correction system that I think could be improved. If felt this system to be too rigid. Maybe allowing people to give points 1 by 1 intead of just a few options (0, 3 or 5 points) would help. I also feel like too many points are awarded for criterias that are beside the point of the course (5 points for the number of pages, 5 points for knowing how to write an abstract, 3 points for redacting the problem to be answered). This skills however important were not taught in this course and are unfair to evaluate in my opinion.

The course was really great for me to start using R and build models. But it was really challenging. And the final peer-graded submission really threw me off due to the late / lousy markings for my submission and lack of available submissions for me to mark. Still an enriching and challenging course overall!

I thoroughly enjoyed participating in this course, and I do think that I learned a fair number of skills of real conceptual and practical value. Thanks to the instructors' team for their dedicated efforts.

Very comprehensive and challenging course. The explanations/rationale could be done better In the statistical programming parts.

Classes are very good, but people do not put much effort on peer review coments.

This course gives a very good introduction to Bayesian modeling in R using MCMC.

The course is very helpful for those who wanted to learn the Bayesian modeling.

The programming examples are excellent. Thank you...

Good balance between courses and codes exercises

I think this course is hard.

I learn a lot, thank you.

This course requires quite a lot of preliminary knowledge on the subject. I had to complete the previous course ("Bayesian Statistics: From Concept to Data Analysis") in order to be able to proceed with this one, and still was apparently missing some essential information towards the end. I would add one more course to fill the gaps and make a specialization out of the three resulting courses.

H​igh quality videos and lots of examples. Nonetheless, in some cases I felt that key concepts (e.g., Metropolis-Hastings algorithm) were only introduced on a technical/formulas level whithout giving an understanding why it works. From time to time, an overview on things would have been nice. E.g., when do I actually use which method. This is why I can only give 3/5.

Te obliga a hacer una prueba final abierta, debiese ser opcional, entiendo sirve para la clasificación, pero si ya aprendiste los contenidos esenciales y no te interesa el curso para certificar ya, lo encuentro innecesario

Such shallow course. You will be better off reading chapter1 of Bayesian data analysis. Don't waste your time here.