This paper presents a current feedback learning controller for dynamic control of DC motors. The proposed controller uses the full third-order dynamics model of DC motor system to drive stable learning rules for virtual current learning input, voltage learning input, and the coefficient of electromotive force. It is shown that the proposed learning controller drives the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one globally asymptotically. Computer simulation and experimental results are given to demonstrate the effectiveness of the proposed adaptive learning controller.