Fundamentals of Bayesian Data Analysis in R
Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.
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Course Description
Bayesian data analysis is an approach to statistical modeling and machine learning that is becoming more and more popular. It provides a uniform framework to build problem specific models that can be used for both statistical inference and for prediction. This course will introduce you to Bayesian data analysis: What it is, how it works, and why it is a useful tool to have in your data science toolbox.
- 1
What is Bayesian Data Analysis?
FreeThis chapter will introduce you to Bayesian data analysis and give you a feel for how it works. - 2
How does Bayesian inference work?
In this chapter we will take a detailed look at the foundations of Bayesian inference. - 3
Why use Bayesian Data Analysis?
This chapter will show you four reasons why Bayesian data analysis is a useful tool to have in your data science tool belt. - 4
Bayesian inference with Bayes' theorem
Learn what Bayes theorem is all about and how to use it for statistical inference. - 5
More parameters, more data, and more Bayes
Learn about using the Normal distribution to analyze continuous data and try out a tool for practical Bayesian analysis in R.
Nick Solomon
Chester IsmayPrerequisites
Introduction to R
Rasmus Bååth
Senior Data Scientist at King (Activision Blizzard)
Rasmus Bååth is a Senior Data Scientist at King. Previously, he was an instructor and Curriculum Lead for Projects at DataCamp. He has a PhD in Cognitive Science from Lund University in Sweden. Follow him at @rabaath on Twitter or on his blog, Publishable Stuff.
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