Nov 01, 2017
This course is excellent! The material is very very interesting, the videos are of high quality and the quizzes and project really helps you getting it together. I really enjoyed it!!!
Jul 08, 2018
This is a great course for an introduction to Bayesian Statistics class. Prior knowledge of the use of R can be very helpful. Thanks for such a wonderful course!!!
par Brian K
•Apr 01, 2019
Excellent course! This covered a large amount of material, but it was well organized, with a good number of problems to solve. Matthew Heiner does an excellent job with the lectures and explains things well. Coming from the frequentist worldview, I found this course to be a definite challenge, but well worth the time.
par Jonathan
•Jan 01, 2019
Just finishing this class now......it is very good. Much better than the first one in this series. The videos and examples are better explained, and you leave with a solid understanding of Bayesian Analysis. When I signed up for this class I really wanted to know how I could use tools like MCMC to perform real analysis, and I feel like I got what I signed up for. Well done!
par Hugo R C R
•Jun 19, 2018
Brilliant course! Very well organized and with useful study cases.Suggestion: It would be nice to have the same examples in Python using, e.g. Stan or PyMC.
par Arnaud D
•Dec 08, 2018
Really interesting course. The coding session are useful and can be use cases for lots of various situations.
par Seema K
•Nov 17, 2019
One of the best designed courses. The material and videos are very precise and informative. The quiz questions and assignment are very enjoyable. Thank you !
par Georgy M
•Apr 01, 2019
The second course of the great series. The knowledge and skills gained in this course allow to actually do statistical analysis on scientific data. The course is very clear, systematic and well presented. Thank you!
par zhen w
•Jul 28, 2017
really like the content.
the R material in this actually changes my view towards R, so thanks.
par Eugene B
•Jun 26, 2019
The course provided a lot of very helpful tools. However, I believe it was a bit too fast paced. Furthermore, there were certain topics which were not explained clearly -- for example, the discussion of the Metropolis-Hastings Algorithm and Gibbs Sampling was extremely confusing.
par Yahia E G
•Jun 06, 2019
Really good intermediate introduction to bayesian analysis. I really liked how hands-on the course is. The last project was very useful as one will likely to face challenges and try to solve them especially if you use a rich dataset.
par Chiu W K
•Jul 29, 2017
Informative but the pace is slow
par Sandra M
•May 14, 2018
Good course, but the peer review process for the Capstone project in Week 5 is broken. Based on submissions to the course Forum in which multiple students have submitted their work on time but not received a grade due to lack of peer reviewers, this has been going on .
par Sathish R
•May 21, 2018
This course is taught in a way that not useful for real world applications.
par Jiasun
•Jul 20, 2019
Not enough depth.
par Wangtx
•Dec 11, 2018
Great materials and well organized lecture structure. But in the meanwhile, it requires quite a lot preliminary knowledge.
par Juan C
•Jan 29, 2019
Muy recomendable para los investigadores y profesionales que quieren desarrollar productos y procesos nuevos.
par Nikola M
•Apr 07, 2019
one of best stats courses I had
par Chen N
•Apr 08, 2019
Amazing, super cool!
par Lau C
•Apr 15, 2019
Super clear and easy to follow. Thanks so much.
par Stephen H
•Mar 18, 2019
Fairly good introduction to basic Bayesian statistical models and JAGS, the package to fit those models.
par Ilia S
•Sep 24, 2018
I found this course very interesting and informative.
par Ahmed M
•Nov 12, 2018
If you want to become good in modelling it is recommended to enrol.
par Dongliang Y
•Sep 30, 2018
Great class.
par Nicholas W T
•Sep 06, 2018
Very thorough instruction. Excellent feedback and support on forums.
par Dallam M
•Jun 27, 2017
great course
par JOSE F
•Feb 11, 2018
Very challenging but interesting!