Bayesian Statistics
Techniques and Models
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Rating | 4.6★ based on 75 ratings |
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Length | 6 weeks |
Effort | 5 weeks of study, 4-6 hours/week. |
Starts | Jul 17 (37 weeks ago) |
Cost | $49 |
From | University of California, Santa Cruz via Coursera |
Instructor | Matthew Heiner |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Mathematics |
Tags | Data Science Math And Logic Probability And Statistics |
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What people are saying
very good
A very good course to introduce yours Outstanding, Excellent, Must do for statistician.
A great course, very detailed and a very good instructor!
Very good part II course in continuation with course I.
Very good and useful course, and hard as well.
Just finishing this class now......it is very good.
Classes are very good, but people do not put much effort on peer review coments.
This course gives a very good introduction to Bayesian modeling in R using MCMC.
Complex subject made easy with easy to understand theory & practical examples Very good course, a little bit to slow at some point but this is marginal in the overall feeling.
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bayesian statistics
Very good course giving a good practical kickoff to a very interesting and exciting topic of Bayesian statistics.
This course is a great start for everyone who wants to dive into Bayesian Statistics.
This course fills an essential gap in learning Bayesian statistics, and provides concrete assistance in moving from theory to actual model writing in R and jags.
However, the course requires a fairly high level of comfort with both general Bayesian statistics and the R language.
great course This course is a perfect continuation of the Bayesian Statistics course by Prof. Herbert Lee.
Excellent for the beginners to the Bayesian Statistics as it allows to start confidently using Bayesian models in practice.
This course follows "Bayesian Statistics: From Concept to Data Analysis".
If you are interested to learn about Bayesian Statistics, I recommend this 2 courses.
A very good practical and theoretical course This is a great course for an introduction to Bayesian Statistics class.
I had to complete the previous course ("Bayesian Statistics: From Concept to Data Analysis") in order to be able to proceed with this one, and still was apparently missing some essential information towards the end.
In this course, professors will guide you on how to build a Bayesian model hand by hand with R. Furthermore, all prior knowledge got from another Bayesian Statistics course can get improved and solid too Awsome course overall.
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quite a lot
terrific, so I've learn quite a lot basic knowledge about MCMC.
But in the meanwhile, it requires quite a lot preliminary knowledge.
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very helpful
The course requires good understanding of Bayesian methods and linear modelling, something that is covered in previous course of this track from University of California Santa Cruz.All quizes are quite easy to complete after watching the videos, but don't be fooled by this apparent simplicity - there is much more to the class than just that.Capstone project is challenging and does put to test all of the topic discussed in class,discussion forums are very helpful and also are extremely interesting to read.I can strongly recommend this class to anyone who is interested in Bayesian Methods.I've seen quite a few of similar classes on Coursera, but this one is the best, in my opinion, but also is the hardest one.Do not miss out on Honors track, recommended supplementary reading and Capstone - those are the gems.
Very helpful!
Prior knowledge of the use of R can be very helpful.
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well organized
This covered a large amount of material, but it was well organized, with a good number of problems to solve.
Great materials and well organized lecture structure.
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points for
I also feel like too many points are awarded for criterias that are beside the point of the course (5 points for the number of pages, 5 points for knowing how to write an abstract, 3 points for redacting the problem to be answered).
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Rating | 4.6★ based on 75 ratings |
---|---|
Length | 6 weeks |
Effort | 5 weeks of study, 4-6 hours/week. |
Starts | Jul 17 (37 weeks ago) |
Cost | $49 |
From | University of California, Santa Cruz via Coursera |
Instructor | Matthew Heiner |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Mathematics |
Tags | Data Science Math And Logic Probability And Statistics |
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