Avis et commentaires pour l'étudiant pour Bayesian Statistics: Techniques and Models par Université de Californie à Santa Cruz

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.

Really interesting course. The coding session are useful and can be use cases for lots of various situations.

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!

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!

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.

Great materials and well organized lecture structure. But in the meanwhile, it requires quite a lot preliminary knowledge.

Muy recomendable para los investigadores y profesionales que quieren desarrollar productos y procesos nuevos.

This course helped me to get some experience at building Bayesian models and how they are applied.

If you want to become good in modelling it is recommended to enrol.

Fairly good introduction to basic Bayesian statistical models and JAGS, the package to fit those models.

A very good practical and theoretical course

Great course to learn both theories and techniques!

Very thorough instruction. Excellent feedback and support on forums.

I found this course very interesting and informative.

Great class.

The course requires good understanding of Bayesian methods and linear modelling, something that is covered in previous course of this track from University of California Santa Cruz.

All quizes are quite easy to complete after watching the videos, but don't be fooled by this apparent simplicity - there is much more to the class than just that.

Capstone project is challenging and does put to test all of the topic discussed in class,

discussion forums are very helpful and also are extremely interesting to read.

I can strongly recommend this class to anyone who is interested in Bayesian Methods.

I've seen quite a few of similar classes on Coursera, but this one is the best, in my opinion, but also is the hardest one.

Do not miss out on Honors track, recommended supplementary reading and Capstone - those are the gems.

A great course, very detailed and a very good instructor!

Great course!

Very cool, probably the best course I've done in Coursera. Keep rocking! :)

This course is a perfect continuation of the Bayesian Statistics course by Prof. Herbert Lee. It's not only mathematically rigorous but also very applied. Excellent for the beginners to the Bayesian Statistics as it allows to start confidently using Bayesian models in practice.

Matthew Heiner is an excellent lecturer. Thank you.

Excellent course. R usage straight from the beginning, a much useful addition to the previous course. It's very complete and when something mentioned and not explained further additional sources are recommended. Lot's of practical work and the final project I found amazing, a very practical approach that should prepare you to write reports and seriously analyse data. I would just recommend to put in the course prerequisites some basic R and some experience with statistics and probability. Although the course can be taken in isolation, the previous one is almost a prerequisite (if bayes thinking is new to you)

great course

Very challenging but interesting!

terrific, so I've learn quite a lot basic knowledge about MCMC. So I can build kinds of models with better understanding.

Very helpful!