# 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.
4 Hours23 Videos58 Exercises16,615 Learners
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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?

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

### How does Bayesian inference work?

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

### Bayesian inference with Bayes' theorem

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

#### Rasmus Bååth

Rasmus Bååth is a Data Science Lead at castle.io. 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.

## What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden