Sep 01, 2017
Good intro to Bayesian Statistics. Covers the basic concepts. Workload is reasonable and quizzes/exercises are helpful. Could include more exercises and additional backgroung/future reading materials.
Jun 27, 2018
Great course. The content moves at a nice pace and the videos are really good to follow. The Quizzes are also set at a good level. You can't pass this course unless you have understood the material.
автор: Mark S•
Feb 08, 2017
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.
автор: Haozhe ( X•
Apr 25, 2020
Great course for intro to Bayesian. Before deciding to learn bayesian, I expect to choose a course which could explain concept in a simple way but, at the same time, having enough practice. This course matches my need. After taking this course, I would recommend it to anyone who want to learn some bayesian for further machine learning studies.
автор: David D•
Feb 27, 2019
Really loved this course. I am relatively new to Statistics but very familiar with the rest of the mathematical tools used in this class (Integration, sets, etc). After finishing the class, I was immediately able to apply Bayesian Inference to my job. Things were explained well, and made sense after re-watching once or twice. Excellent course!
автор: Polano M•
Mar 11, 2018
Great introduction to Bayesian Statistics.
Prof. Lee uses the right approach with a theoretical introduction that helps to graps the concepts with a right balance of math and intuition. This was my first exposure to the bayesian approach to statistics and after this course I want to learn more, both on the pratical and the theoretical side.
автор: TERENCE Y•
Sep 19, 2017
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.
автор: Brandon H•
Mar 07, 2018
This is a great course! Much better (and cheaper) than the course I took in grad school. Full of practical knowledge, and isn't too overwhelming on the mathematics/statistical theory. It's just right. Good for anyone interested in Bayesian statistics, though some background with probability distributions may help climb the learning curve.
Dec 27, 2016
I really enjoyed this course. The lectures were short and clearly explained, and particularly highlighted why Bayesian statistics is different and what is useful about it. I would have like a bit more walk-through on some of the derivations in weeks 3 and 4. More R exercises and further resource recommendations would have been useful.
автор: Galley D•
Sep 11, 2017
Outstanding course to understand Bayesian statistics. Teacher is very pedagogical and the course delivery with equations written on the transparent board make everything easy to follow.
As an area for development, I would have like more information on Bayesian linear regression in week 4, through background lecture or dedicated video.
автор: Fedor T•
Jan 21, 2017
Very clear lectures masterfully delivered by prof. Lee. The quizzes are good, if somewhat on the easy side. Don't be discouraged by the choice of R as the tool for assignments. R is flawed as a programming language, but you won't need to do any programming, only one-liners to evaluate various statistical functions and plot results.
автор: Nathaniel R•
Nov 21, 2016
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!
автор: Musa J•
Aug 11, 2017
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.
Sep 11, 2016
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.
автор: Victor A•
Mar 01, 2017
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
автор: Kevin L•
May 25, 2020
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.
автор: John G•
Oct 30, 2017
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.
автор: William P•
Aug 03, 2018
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.
автор: Guido W R•
Oct 05, 2016
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.
автор: Oaní d S d C•
Apr 22, 2018
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.
автор: Derek H•
Jun 12, 2019
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.
автор: Devesh S•
Jun 30, 2017
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.
автор: Manuel M S•
Apr 29, 2020
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!
автор: Xiaomeng W•
Dec 13, 2019
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).
автор: Sujith N•
Feb 24, 2018
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.
автор: Mikhail G•
Jun 06, 2020
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'.
Apr 28, 2019
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".