The aim of this course is to present important concepts of time series analysis such as stationarity, stationary time series models (MA, AR, ARMA models), tends and methods for dealing with non-stationarity, nonstationary time series models (ARIMA models, SEASONAL MODELS etc.), parametric estimation, model diagnostic, forecasting, heteroscedasticity time series models, and other selected topics such as Co-integration and Causality, etc.). The course focuses bothe on the theory of linear time series and on the practical applications with R.