This document corresponds to a 2h class on kriging, also known as conditional Gaussian Processes (GP) or Gaussian Process Regression (GPR). The class was part of the MNMUQ2019 summer school on uncertainty quantification. In the first part of the class, we introduce basics of GPR up to a point where it could be coded by a motivated student. The second part of the class covers research topics such as kernel design and interpolation in a RKHS.