Stochastic and dynamic optimization are key paradigms arising in multi-stage decision making under uncertainty. In this lecture, we present fundamentals on theory and algorithms and discuss available software tools. We will motivate these concepts through applications arising in the electrical power grid. We will also motivate some discussion by summarizing some of the open research questions in the area