  In these lecture notes, we survey the landscape of Calabi-Yau threefolds, and
the use of machine learning to explore it. We begin with the compact portion of
the landscape, focusing in particular on complete intersection Calabi-Yau
varieties (CICYs) and elliptic fibrations. Non-compact Calabi-Yau manifolds are
manifest in Type II superstring theories, they arise as representation
varieties of quivers, used to describe gauge theories in the bulk familiar four
dimensions. Finally, given the huge amount of Calabi-Yau data, whether and how
machine learning can be applied to algebraic geometry and string landscape is
also discussed. These notes are directed to the beginning graduate student
interested in mathematics and in physics, and are based on lectures given by
the 2nd author at the 2019 PIMS Summer School on Algebraic Geometry in
High-Energy Physics at the University of Saskatchewan.
