Learning to play the guitar is a long and tedious process and many would-be players struggle at it. Specialized software applications can help music students and self-taught musicians by providing additional insights at the errors made during the learning process. This bachelor thesis describes the development of a prototypical visualization application for the use in musical education. It provides an overview of the theoretical background and technical requirements and describes the conception, implementation and evaluation of our prototype. We use MIDI data, which we receive from a polyphonic pickup that we mounted to a guitar. Our prototype consists of three visualizations that allow to analyze live input of this MIDI data, perform error detection, and see general patterns in a summary heat map of multiple MIDI recordings. As part of a user-centered design, we first collected requirements from a group of guitar players and a guitar teacher, and later evaluated our prototype with them. This evaluation revealed several limitations, but also showed that our concept can be useful to support beginners in learning to play guitar.