We propose the use of the extreme learning machine in programming by demonstration. Some advantages of this technique are a fast training phase and avoiding falling in local minima. We present two ways of using it:(i) for encoding one or several trajectories of a demonstration and (ii) for learning the direct kinematic model of a robot, which once known, allows changing the final position of the demonstrated trajectory. Through comparison with other commonly used techniques, it is experimentally shown that this technique has the