The biological brain has the capability of learning, pattern recognition, processing imprecisely defined data and executing complex computational tasks. Consisting of 10¹¹ neurons and 10¹⁵ synapses as the major computational components, the biological brain is extremely power efficient, massively parallel, structurally plastic, and exceptionally robust against noise and variations. Development of efficient electronic synapses is essential for building large-scale neuromorphic systems. In this talk, we will present synaptic devices based on phase change memory (PCM). We will first explain basics of phase change synaptic devices: device operation, phase change materials, conduction mechanism, power consumption and scaling. We will then discuss the use of PCM for synaptic device implementations spanning from single device operation to various array architecture designs. The concept of spike timing dependent plasticity (STDP), various pulse scheme designs, and pulse programming techniques for plasticity will be explained. Last, we will present implementation of learning using PCM crossbar arrays.