In this talk we will give a gentle introduction to Deep Learning using Python with the help of Lasagne, Numpy, Pandas and OpenCV having fun with Star Wars miniature ships in the process. We will walk through the pipeline, starting from data acquisition, preparation, construction of ConvNets, training and assessment, in order to classify different types of ships! Deep Learning allows computational models that are composed of multiple processing layers to learn representation of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Particularly, Convolutional Neural Networks (ConvNets) represent the state of art of several computer vision problems, given its outstanding classification performance in large volumes of images. ConvNets great performance is based on four fundamental ideas. Local connections, shared weights, pooling and the use of multiple layers. For this talk we will have miniatures ships in the room so participants can record their own videos, and use it as data source for their own classifiers! During the talk we will show how to classify k-wing, lambda shuttle and millennium falcon miniatures.