This is a crash course that explores the notions of why Thick-Tailed distributions or more popularly known as Fat Tails are often an avoided nightmare in statistics. In simple words Fat Tails are remote or rare events that have a low probability of occurring but when they happen they command a much greater effect and break any naive model build on training data that ignored such events.

The concepts are synthetized in Jupyter notebooks and use Nassim Taleb's lectures, his book Statistical Consequences of Fat Tails and some papers from his unofficial website