This paper describes the implementation of RNN (Recurrent Neural Network) to predict future price movements of a cryptocurrency based on a sequence. Using 4 crypto/fiat pair historical (last 60 minutes) of 1 minute tick prices and volumes, the RNN predicts if the selected crypto/fiat pair price will rise or fall 3 minutes in the future (classification problem). This is a deep learning exercise using Python, Tensorflow & Keras. Crypto/Fiat pairs used in this analysis are BTC/USD, BCH/USD, ETH/USD & LTC/USD.