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. 1

    What is Bayesian Data Analysis?

    This chapter will introduce you to Bayesian data analysis and give you a feel for how it works.
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  2. 2

    How does Bayesian inference work?

    In this chapter we will take a detailed look at the foundations of Bayesian inference.
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  3. 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.
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  4. 4

    Bayesian inference with Bayes' theorem

    Learn what Bayes theorem is all about and how to use it for statistical inference.
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  5. 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.
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In the following tracks
Machine Learning ScientistStatistician
Nick SolomonChester Ismay
Introduction to R
Rasmus Bååth Headshot

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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