From the discussion above, it is clearly that developing any PES is consisted of the following three components: sampling data, determining their electronic energies, and fitting them to a specific function. This is essentially similar to machine learning (ML), which enables the computers to address problems by learning from data. Apparently, data locates at the core position: no data, no learning; bad data leads to "wrong" learning, namely, unreliable PESs. In this Chapter, we will restrict the discussion to data quality, data sampling and data fitting for the PES development of small gas-phase molecular systems, reactive or non-reactive. It is not our purpose to provide a comprehensive and rigorous review of all relevant investigations. Instead, we provide a tutorial guide for developing fulldimensional accurate PESs of small molecular systems based on a large number of datasets, whose electronic energies are computed at the CCSD(T) or MRCI level.