Different classes of nonconvex nonsmooth stochastic optimization problems are analyzed, their generalized differentiability properties and necessary optimality conditions are studied, and a technique for calculating stochastic gradients is developed. For each class of the problems, corresponding solution methods are proposed, in particular, generalizations of the stochastic quasigradient method.