PyMC provides advanced MCMC sampling algorithms including the No U-Turn Sampler (NUTS) and variational inference methods like ADVI for approximate posterior estimation. It relies on PyTensor for automatic differentiation and computational optimization, offering an intuitive probabilistic programming API where models are specified declaratively similar to statistical notation.