I found this course to be really useful. It did progress through the math a bit quickly for my liking, but it was paced very appropriately and the discussion forums were helpful. Excellent examples are contained and I loved how both R and Excel modules were leveraged. Looking forward to seeing more Bayesian courses on Coursera in the future.

Prof Lee derived the formulas in an upbeat way, which helped me learn. I'd suggest putting the actual lectures into pdf for later reference, like is done for supplementary material. Homework assignments were challenging and educational. You might suggest a review of prob distributions as pre-requisite.

Very well presented course. Interesting and intuitive introduction into the fascinating Bayesian world.

Many thanks and congratulations!!!

A concise and clear introduction to the Bayesian paradigm. Its conciseness make it suitable for frequentists wanting to get a quick overview of the Bayesian Way.

Good course. This course is quite challenging for people who don't major in math or physics. However, it isn't so difficult to understand as the post half of this course has a lot in common. In my experience, understanding the concept of priors and posterior estimation is the core of this course. Have fun learning this course.

This course helped me a lot in getting a better understanding of Bayesian methods. I recommend this course for all data scientists and machine learning practitioners.

I really like the assignments, they are very well designed and helped a lot in consolidating my understanding of the topic. In my opinion, these assignments are the reason why coursera courses are better than the video lectures available elsewhere.

I took this course due to my interest in machine learning and graphical models. I like the approach and execution. I recommend it for anyony interrested in statistical inference. Some topics require looking up external sources, like wikipedia, but it is not an issue.

Learned something new :). Lecture were excellent, but, I need time to digest and hope I will get opportunity to use it in future.

An excellent introduction to Bayesian Analysis with some practical examples and applications. The lessons serve as a solid foundation towards understanding the philosophical underpinnings of the Bayesian approach to decision analysis under uncertainty. Thanks to Prof Herbert Lee for making the easy to understand without sacrificing rigour.

The course manages very well to balance out comprehensibility and content. Professor Herbert Lee has obviously prepared the material very thoroughly and imparts the content of the course in an enjoyable fashion.

Very good, I reccomend it to data scientist

Very nice course that in my opinion nicely fits between Bolstad and Gelman in difficulty (talking in popular Bayesian Data Analysis books). Herbert Lee does a very good job at building one's intuition and understanding in the general Bayesian inference. Good starting point for moving on with Bayes.

Exceptional course on probabilities and statistics from a Bayesian point of view. I would recommend this course to anyone wishing to learn more about probabilities and statistics.

As a primer to Bayesian Statistics, this course covers the basics at a brisk pace. No time is wasted in explaining the basics of Probability theory; which I have always found, at best, to be distracting in the other similar courses I have taken. Thank you, Herbert Lee and Coursera.

Very interesting. It can help taking notes during the course... to avoid going again through it and take them ex-post.

Become very clear about all the formula and derivation of Bayesian Statistics after taking this course. Strongly recommended.

Great course! Well explained with useful additional material. Strongly suggested.

A clear and compact introduction. Quizzes and exercises are relevant. I got acces to grades and feedback in the audit one I took.

Very interesting course.

For me the most interesting and important themes are about priors:

1) conjugated priors

2) effective prior size

3) how to choose a prior

4) non-informative priors

5) improper priors

6) Jeffreys priors

Herbert Lee's Tests are fun (Best!) to learn during the test! Lectures are succinct; Format of writing on the glass towards you and then flipped was right & original. Went on to try Kaggle problems independently. For usable feedback need tiny bit more on Poisson, Gamma, non conjugate intuitively & darker shirts as background.

A step by step course, designed to pay attention all the time with tons of practical examples and very clear explanations, I would definitely recommend it!!

This course are excellent and Thanks for Prof for offering the course. I've learned a lot from the course. Thank you.

It is the good place to start to learn Bayesian theory

A great course on Bayesian Statistics.