In this paper we build a dataset of Italian syllables. We perform quantitative and qualitative analyses on the syllabification and stress assignment in Italian. We propose a machine learning model, based on deep-learning techniques, for automatically inferring syllabification and stress assignment. For stress prediction we report 94.45% word-level accuracy, and for syllabification we report 98.41% word-level accuracy and 99.82% hyphen-level accuracy.