1. A learning method of a semiconductor device comprising a neuro device having a multiplier as a synapse in which a weight varies according to an input weight voltage, and functioning as a neural network system that processes analog data, the learning method comprising: a step A of inputting predetermined input data to the neuro device and calculating an error between a target value of an output of the neuro device with respect to the input data and an actual output; a step B of calculating variation amount in the error by varying the weight of the multiplier thereafter; and a step C of varying the weight of the multiplier based on the variation amount in the error, wherein in the steps B and C, after inputting a reset voltage for setting the weight to a substantially constant value to the multiplier as the weight voltage, the weight is varied by inputting the weight voltage corresponding to the weight to be varied.