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Prerequisites: Course Contents Review of discrete probability; Notion of randomized algorithms, motivating examples; Markov, Chebyshev inequalities, Chern off bounds; Probabilistic method; Hashing, fingerprinting; Random walks and Markov chains. Program checkers; Polynomial identities; Randomized complexity classes, Probabilistically check able proofs; some number theoretic problems; Approximate counting. Topics
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