This is the first online course I have ever taken so I don't have anything to compare it to, but this course was excellent! The lectures and materials were very clear and I will be adopting some of Prof. Lee's approach into my own teaching practice. The bar has been set very high for any future online courses that I will take!

Herbert Lee provides a sound introduction to Bayesian statistics while also offering, to the attentive learner, an analysis of the frequentist paradigm (e.g. the pitfalls of making objectivity assumptions and using p-values). The course requires less math background from the learner than it helps building. Highly recommended!

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.

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.

It's a great course, there is a lot of information and it might seem at times overwhelming, but it's organized nicely and prof. Lee has a very comfortable time explaining all the concepts. A few more examples would have made this course easier, but that does not mean it would have been better. It's as good as it gets

This course offers great explanations about Bayesian statistics. Although the course is a bit hard, by understanding each example provided in each lecture, I was able to grasp the basic concepts and ideas about Bayesian statistics. Also, I am now able to use R for Bayesian statistics thanks to this course.

This is a great course for anyone with no prior knowledge of Bayesian statistics. The instructor did a great job explaining the concepts and provided good examples. I also liked the quizzes and activities in R/Excel. I learned a lot from this course! I plan to take a few more courses in Bayesian stats.

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.

Fantastic first course. The only concern I have is with the software choices. I have neither R nor Excel, but was able to easily use google Sheets. It might be worth mentioning to students that this is an option. There is even a stats package that claims parity with one of the listed packages for excel.

The quizzes in the course are very well elaborated and designed to help you learn points and details not explicitly stated in the lectures. The contents and pacing are just about right for me. Perhaps the section on normal inference would need more elaborated as this part was the most difficult for me.

This course provide the theoretical basics for anyone who wants to understand, and hopefully work with, Bayesian stats. Prof. Lee's exposition of the math behind Bayesian stat is precise concise and to the point. If I, with only high school math from age ago, could understand, I believe anyone can.

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.

Amazing. Simple, fast, dense, very well taught. I loved the professor, his commentaries and way to explain the contents. Thought the exercises were OK, maybe simpler than I taught but the comments in them helped me a lot to understand the topics. 10/10, a new and better way to teach! Very useful.

Un curso muy bueno, sobre un enfoque de la estadística que desconocía. Además de reforzar muy bien las cosas que ya sabía y darles ese enfoque Bayesiano. Me gusta que todo se resume en la importancia de la probabilidad condicionada, ya que el teorema de Bayes conjuga las probabilidades inversas.

Good to learn or re-learn the basics of statistic and probability, and as a foundation for learning maximum likelihood methods (which are much more useful later on). The material is digestible, to the point, and the quizzes are helpful in checking your understanding and information retention.

This is an absolutely fantastic course for anyone interested in Bayesian Statistics. It is certainly not an easy course to cruise through and I highly recommend thoroughly experimenting with the concepts taught in the videos. I had a great time learning from Prof. Herbert Lee, he is amazing!

A well organized course, learned important concepts in statistics and probability that will definitely help anyone wanting to specialize in machine learning or take up data science. Clear and concise explanation of theory focusing on application that is adequately tested in the exams.

An excellent course on the basics of Bayesian approach to statistics. It has excellent explanations, from the concept to applications and allows gaining understanding both on the basic underlying ideas, as well as a deeper insight on Bayesian methodologies. I definitely recommend it!

I've reviewed probabilities and basic Bayesian methods in this course. The quizzes have good explanation and the additional reading materials are helpful. I'm learning the next course: Techniques and models, which is also great (except that we don't have free access to the quizzes).

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.

An interesting course which gives an opportunity not only to study some purely 'technical' skills but also to think a bit about statistical problems in a broader context. It won't make you 'Bayesian', however, it will help to understand the philosophy of this statistical 'sect'.

There are books and courses out there teaching you how to use machine learning tools to solve real problems. But there aren't so many like this starting from the Bayesian way. Besides, this is a good entry point for me to read the book "Pattern Recognition and Machine Learning".

I have signed up for this course because I encountered Bayesian concepts through work (automotive industry), and I wanted to improve my understanding of the underlying basics. What can I say, my expectations have been met! Thanks for offering this course through this platform!

Excellent introductory course to bayesian statistics. I'd like to thank Professor Lee, University of Santa Cruz, Coursera and all supporting staff for the opportunity. I'd enjoy if you provided intermediate and advanced courses on bayesian statistics that covers more topics.

Great course. Very clear introductory overview of Bayesian statistics and differences/similarities with the frequentist approach. Well balanced between video lectures, support materials, quizzes and hands-on problems. Looking forward to the next step - hierarchical models.