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Gear up for jobs in high-demand fields: data analytics, digital marketing, and more.In this course, we will cover topics which lie at the intersection of Deep Learning and Generative Modeling. We will start with basics of joint distributions and build up to Directed and Undirected Graphical Models. We will then make a connection between Graphical Models and Deep Learning by having an in-depth discussion on Restricted Boltzmann Machines, Markov Chains and Gibbs Sampling for training RBMs. Finally, we will cover more recent Deep Generative models such as Variational Autoencoders, Generative Adversarial Networks and Autoregressive Models.