Rough paths is a mathematical framework that extends the theory of controlled differential equations to incorporate paths of low regularity, crucially allowing the analysis of stochastic processes. This approach provides the tools necessary to rigorously handle highly irregular signals by giving meaning to ambiguous integrals, which facilitates advancements in a wide range of applications from finance to machine learning.