Chevron Left
Back to Introduction to Bayesian Statistics

Learner Reviews & Feedback for Introduction to Bayesian Statistics by Databricks

3.6
stars
39 ratings

About the Course

The objective of this course is to introduce Computational Statistics to aspiring or new data scientists. The attendees will start off by learning the basics of probability, Bayesian modeling and inference. This will be the first course in a specialization of three courses .Python and Jupyter notebooks will be used throughout this course to illustrate and perform Bayesian modeling. The course website is located at https://sjster.github.io/introduction_to_computational_statistics/docs/index.html. The course notebooks can be downloaded from this website by following the instructions on page https://sjster.github.io/introduction_to_computational_statistics/docs/getting_started.html. The instructors for this course will be Dr. Srijith Rajamohan and Dr. Robert Settlage....

Top reviews

Filter by:

1 - 16 of 16 Reviews for Introduction to Bayesian Statistics

By Howard S

•

Jul 5, 2021

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

By Tyler W

•

May 23, 2021

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.

By Yi C

•

Aug 6, 2021

Content is okay, but a better teaching is needed.

By Mars G

•

Aug 14, 2021

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!!

By kulbhushan s

•

Nov 4, 2023

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.

By Flavio L

•

Jan 24, 2022

amazing, nice material, well explained

By Lawrence A J

•

Apr 25, 2023

Good introduction and background.

By Shahid R

•

May 24, 2023

Amazing Course

By stephane d

•

Nov 11, 2021

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.

By Taranpreet s

•

Feb 26, 2022

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.

By Anupam G

•

Jul 21, 2021

Rather an easy course to follow.

By Charles W C I

•

Oct 14, 2022

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.

By Eli K

•

May 18, 2021

A course based on notebooks is not very convenient.

By Jaroslav H

•

Jun 20, 2021

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"

By Bob W

•

Jul 27, 2021

I'd give it 0 stars if I could. The teaching style is very poor. Details are severaly lacking, and there are many mistakes in the course notebooks. I don't recommend this course. Instead look to one given by a reputable university.

By Felix R

•

Jul 17, 2021

Really hard to access and use Databricks. Disappointing that this is my first course on this website. Wouldn't recommend. Appallingly set out course. Would give it 0 stars if I could. Beginners stay away!