A Q-learning based current-steering digital to analog converter (DAC) calibration method is proposed in this paper for spurious-free dynamic range (SFDR) improvement. A look-up table (LUT) to control the switching sequence of the DAC elements is achieved by Q-learning for an optimal SFDR. Compared with the fixed element transition strategy proposed by manual derivation, the LUT can be updated by off-line training to deal with diverse and complex non-ideal factors limiting the SFDR of DAC.