Bayesian Data Analysis Its Applications

The recent changes in information environments have led to the increases in demand for the ability to collect, process, and interpret data. This course introduces Bayesian statistics, which serves as the theoretical foundation of cutting-edge machine learning techniques and artificial intelligence. The core concepts in probability theory and the logics behind statistical inference will be introduced using examples of everyday problems. Starting from the science behind Sherlock Holmes' investigation methods, the lectures will cover various creative topics, including predicting the divorce of celebrity couples and the winner of best picture at the Oscars, forecasting free-food events on campus, classifying spams from legitimate emails, and many other applications of Bayesian methods. This course also emphasizes the development of practical skills, offering an opportunity for students to learn programming languages, such as R and Python. A series of tutorials will cover from the basic to intermediate level coding skills for writing algorithms of machine learning. No prior knowledge of programming is expected.