Great content, short explanations of complex topics are well explained, but there are unacceptable number of typos and grammatical errors in the accompanying notebooks. It's very obvious from the alarming number of mistakes that none of the content was proofread before publishing.

Needs a better instructor. Course is very dry and boring.

This course would be a bit hard for "complete" beginners, but would be enough for people who wish to refresh knowledge about Bayesian inference and stuff. The notes and codes are very good!!

Content is okay, but a better teaching is needed.

Title: Introduction to Bayesian Statistics - A Comprehensive Overview The "Introduction to Bayesian Statistics" provides a thorough and accessible introduction to the fundamental concepts and techniques of Bayesian statistics. The course effectively bridges the gap between theory and application, making it suitable for both beginners and those with some prior statistical knowledge. One of the strengths of this course is its clear and well-structured presentation. The instructor does an excellent job of breaking down complex concepts into digestible chunks, ensuring that even those new to Bayesian statistics can grasp the material. The use of real-world examples and practical exercises further enhances understanding and reinforces key concepts. The course covers a wide range of topics, from the basics of Bayes' theorem to more advanced topics like Markov Chain Monte Carlo (MCMC) methods. This comprehensive coverage ensures that learners gain a solid foundation in Bayesian statistics and are equipped to tackle more complex problems in the future. The "Introduction to Bayesian Statistics" is a valuable resource for anyone looking to gain a solid understanding of Bayesian statistics. Its clear presentation, comprehensive coverage, and practical examples make it a highly recommended course for both beginners and those looking to deepen their knowledge in this field. With a few added interactive elements, it has the potential to be even more effective in facilitating learning.

i think some parts in the course could have been more engaging overall good course, But the material taught seemed more vast as compared to the practice sheets. Still good to get into and explore more about probabilities and Bayesian Statistic

amazing, nice material, well explained

Good introduction and background.

Amazing Course

nice course

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ITS GOOD

v good

good

GOOD

Clear explanations with lots of small examples to illustrate the material. The text provided in the slides is interesting but it should just be provided in support of the code and the slides should be used to show visual examples. I still recommend this course.

Content/notes wise this course is great, But teaching style needs to be improved. Rather than reading the notes instructor should teach by giving examples and driving some of the results.

Rather an easy course to follow.

very good course

thank you

good

There were nuggets of useful information in this course. But overall, I found the lecture style very tedious, and far too academic. Far too many integral signs, and far too few worked practice examples. I'm hoping the next two in the series are better, and more focused on the practitioner looking to solve business problems.

A course based on notebooks is not very convenient.

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Terrible. The worst coursera class I ever took.

A) The quizzes contained errors, incomplete transformations for solving a problem

B) The prof. just showed a page in the book and read from it in a monotonous voice. In

order to understand anything I actually had to stop video and read this page from the book.

B) Prof never actual taught or explained anything, but just glossed over the subject. This hardly be called "teaching"