This thesis provides information on advances in the field of building energy management and efficiency by developing an educational platform that uses machine learning tech- niques such as surrogate modeling and reinforcement learning, for the students and users to better understand how energy management and efficiency works depending on different building parameters by introducing the use of IoT capable sensors and actuators making it possible the user awareness at all times. Also, this platform is intended to facilitate the EneryPlus input data files (IDF) edition by delivering an intuitive graphical user interface (GUI) to add the relevant components for making experiments on building behavior and for exporting models into FMUs in order for the user to work with external interfaces.