This chapter is meant to familiarize readers with the style and structure of the textbook and to outline prerequisite mathematical knowledge. The first three sections are about Calculus, Probability Theory, and Linear Algebra. It is assumed that readers are familiar with the topics, so those sections will mainly be setting notation and explaining how Python can be used to compute results. The last section will be on Gaussian Ensembles, which might be new to many readers. Gaussian Ensembles are the most studied Random Matrices and will be the only class of matrices used in this textbook. In particular we will study the following ensembles

• Gaussian Orthogonal Ensembles
• Gaussian Unitary Ensembles
• Ginibre Ensemble

There are far more ensembles than the ones listed above, but this list is sufficiently interesting and suffices for main results presented in this text.