Rasmus Bååth
Rasmus Bååth

Senior Data Scientist at King (Activision Blizzard)

I'm a Data Scientist at King (Activision/Blizzard) and previously I've been an instructor at DataCamp. I once did a PhD in Cognitive Science at Lund University. I'm passionate about Bayesian statistics, good graphs and free coffee. Follow me @rabaath on Twitter or check out my blog, Publishable Stuff.

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    Chester Ismay

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    Nick Solomon


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.

  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.