This talk is about Google Earth Engine-GEE, a cloud-computing platform capable of processing petabytes of Earth science data and presenting the result of planetary-scale analysis on-the-fly. You will learn about the main concepts, its architecture and the best practices to incorporate GEE in your workflow. For this, I will present a hands-on, using R (rgee), to generate a land-cover classification for a Landsat scene in the Amazon forest (226/67), which will considerer all the landsat images obtained for 2019, a Random Forest model and a hyperparameter optimization implemented in MLR3.