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This book is an accessible introduction to stochastic integration for students with background in advanced calculus and elementary probability theory. Further, the author incorporates methods from measure theory as well as a bit of elementary Hilbert space theory as applied to L2 spaces. There are clear examples used to motivate the concepts and to illustrate the theorems, along with many exercises at the end of each chapter. Topics include constructions of Brownian motion, the Ito formula, stochastic integrals for martingales, and stochastic differential equations. This text is based on lectures first given in 1998, and has been used since then for courses taught by the author at Louisiana State University.