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In this talk, I will introduce the basics of differential privacy and discuss different basic algorithms, such as the exponential mechanism and clipped stochastic gradient descent. I will relate it to Bayesian Sampling and explain how to make them fast using various tricks in MCMC and randomized algorithms.