This brief introduction, without pretension, aims to give some help to non-specialists of statistics to find their way in regression models. What are the basic notions of a regression? A regression model can be linear, generalized linear, nonlinear. Statisticians speak also of parametric, semiparametric, nonparametric regression models. We hope that what is behind these terms will be made clearer after the reading of chapters devoted to simple linear regression, multiple linear regression, logistic regression, survival data and regression, kernel methods... But it can be interesting to have a global view, before reading these chapters, on a rather wide range of regression methods, and to have a first sight on what type of question a particular regression model is answering and what can be expected from such a model on the ground of modelling the data we have in hand.