This cours is devoted to the main problems of the sequential analysis: sequential estimation and sequential hypothesis testing. Firstly we construct the least square estimator for the scalar regression model and then we propose the sequential least square estimator for the autoregression models. Finally, we study the non asymptotic properties for the sequential estimation procedures. Then in the second part of this cours we construct and study the sequential Wald procedure for hypothesis testing. We study its main properties: the mean times and the optimality properties in the sens of minimal mean time. Then we consider some examples of the Wald procedures.