Many planning applications are difficult to model in standard domain description languages. However, with out the limitations of a particular language, it is often possible to obtain or construct an exact or approximate simulator of the application domain. Monte-Carlo planning is an area that studies algorithms for sequential decision making when such a simulator is available. In recent years, advances in Monte-Carlo planning have lead to significant advances in applications ranging from computer networking, to real-time strategy games, to computer Go. This tutorial will cover the basic principles and theory underlying Monte-Carlo planning and also the recent advances. Emphasis will be placed on practical approaches with illustrating applications. The tutorial will start from first principles and will not assume prior knowledge of Monte-Carlo techniques.