I have been teaching the course titled “Bayesian Data Analysis” for almost 8 years now at the University at Albany. Here is a course description:

Course Description: Introduction to both the principles and practice of Bayesian and maximum entropy methods for data analysis, signal processing, and machine learning. This is a hands-on course that will introduce the use of the MATLAB computing language for software development. Students will learn to write their own Bayesian computer programs to solve problems relevant to physics, chemistry, biology, earth science, and signal processing, as well as hypothesis testing and error analysis. Optimization techniques to be covered include gradient ascent, fixed-point methods, and Markov chain Monte Carlo sampling techniques.

I usually use Sivia and Skilling’s text titled “Data Analysis: A Bayesian Tutorial” as the required textbook.

However, recently several of my close colleagues Wolfgang von der Linden, Volker Dose and Udo von Toussaint, have published a new text titled “Bayesian Probability Theory: Applications in the Physical Sciences”

I am going to buy my copy today!