Training is a process to improve one's capacity or performance through the acquisition of knowledge or skills specific for the task. Although behavioral performance would be improved monotonically and reach a plateau as the learning progresses, neurophysiological process shows different pattern like an inverted U-shaped curve. One possible account for the phenomenon is that the brain first works hard to learn how to use specific task-relevant areas, followed by improvement of efficiency derived from disuse of irrelevant brain areas for good task performance. In this study, we employed the functional connectome approach to study the changes in global and local information transfer efficiency of the functional connectivity induced by training of a piloting task. Our results have demonstrated that global information transfer efficiency of the network, revealed by normalized characteristic path length in beta band, once decreased and then increased during the training sessions. We show that graph theoretical network metrics can be used as biomarkers for quantifying the degree of training progresses, in terms of efficiency, which can be differed based on cognitive proficiency of the brain.