As Distributed Acoustic Sensing (DAS) continues to accumulate popularity in numerous applications, the need for automatic processing intensifies. As we witness audio, image and video being analyzed exceptionally using deep learning technologies, one may ask – how can I utilize this knowledge to DAS data processing? The answer is complex and not straightforward since DAS data is unique, with multiple noise sources, stochastic nature and non-existing labeled dataset. In this workshop, I will review deep learning methodologies, the challenges that the DAS data encapsulate for this task, and how they can be tackled.