This course covers statistical models, methods and techniques used in natural language processings. Topics include: Probability, Bayes' methods, entropy and cross entropy of a language, hidden Markov models, Viterbi algorithm, forward-backward algorithm, trigram models, part-of-speech tagging, probabilistic context-free parsing, inside-outside algorithm, learning probabilistic context-free grammars, statistical models of syntactic disambiguation, and word-sense disambiguation.