Quasi-Monte Carlo (QMC) methods are deterministic versions of the classical statistical Monte Carlo methods and they are playing an increasingly important role in scientific computing. The basic idea of QMC methods is to replace the random samples that are used in the implementation of a Monte Carlo method by judiciously chosen deterministic points. QMC methods outperform Monte Carlo methods in many challenging problems of scientific computing, such as those arising in computational finance, computational physics, and computer graphics. The talk will give a quick introduction to QMC methods and then focus on topics in QMC methods of current interest, among them constructions of suitable deterministic points and randomized QMC methods.