In this tutorial we discuss sequential prediction problems in which the forecaster has limited information about the past outcomes of the sequence. We concentrate on the so-called "adversarial" framework in which no probabilistic is available for the sequence. We describe various models of limited feedback and pay special attention to the so-called "multi-armed bandit" problem. We discuss various randomized prediction methods and analyze their behavior.