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Learner Reviews & Feedback for Bayesian Statistics: Techniques and Models by University of California, Santa Cruz

399 ratings
131 reviews

About the Course

This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our “Bayesian toolbox” with more general models, and computational techniques to fit them. In particular, we will introduce Markov chain Monte Carlo (MCMC) methods, which allow sampling from posterior distributions that have no analytical solution. We will use the open-source, freely available software R (some experience is assumed, e.g., completing the previous course in R) and JAGS (no experience required). We will learn how to construct, fit, assess, and compare Bayesian statistical models to answer scientific questions involving continuous, binary, and count data. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. The lectures provide some of the basic mathematical development, explanations of the statistical modeling process, and a few basic modeling techniques commonly used by statisticians. Computer demonstrations provide concrete, practical walkthroughs. Completion of this course will give you access to a wide range of Bayesian analytical tools, customizable to your data....

Top reviews

Oct 31, 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!!!

Nov 23, 2020

I learned a lot about MCMC. This course is taught using R, but I personally was also working on it in python at the same time. I would love to try a higher class. Thank you!

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76 - 100 of 130 Reviews for Bayesian Statistics: Techniques and Models

By Gustavo M

Aug 26, 2019

Very nice course. A bit more theory on sampling methods would be welcome.

By Alejandro D O

May 13, 2020

Excellent, balanced (theory and practice) course. I enjoyed very much.

By Peter W

Aug 8, 2020

Very pleased with the course. It was well worth the time and effort.

By Nicholas W T

Sep 6, 2018

Very thorough instruction. Excellent feedback and support on forums.

By Ahmed M

Nov 12, 2018

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

By Razik R M T

Jan 14, 2021

Great explanations. The instructor made it so easy to understand.

By Emma S

Nov 20, 2020

I absolutely loved this course! Challenging and interesting!

By Stephen B

May 29, 2019

Best course done to date. I wish they had one in STAN too!

By nicole s

Nov 7, 2017

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

By Paramita C

Feb 28, 2021

The material was excellent and the videos were awesome!

By Ilia S

Sep 24, 2018

I found this course very interesting and informative.

By Ken A

Jan 27, 2020

Excellent course. Streamlined but extremely useful.

By Hsiaoyi H

Jul 31, 2018

Great course to learn both theories and techniques!

By Anuj K P

Aug 1, 2020


By Arkobrato G

Nov 11, 2019

Great course with challenging assignments and de

By Enrique A M

Nov 7, 2020

Thanks Teacher Matthew Heiner, Thanks Coursera.

By Lau C

Apr 15, 2019

Super clear and easy to follow. Thanks so much.

By Tibor R

Apr 20, 2019

Very good and useful course, and hard as well.

By Victor Z

Jul 30, 2018

A very good practical and theoretical course

By Farrukh M

Jul 25, 2017

I appropriate the way the course is taught.


Oct 19, 2020

Very nice course, simple and comprehensive

By Evgenii L

May 2, 2018

A very good course to introduce yours

By Luis H

Jul 30, 2017

Rather useful and easy understanding


Feb 11, 2018

Very challenging but interesting!

By Nikola M

Apr 7, 2019

one of best stats courses I had