A question for those who are computational physicist: Dear Computational physicist, I am struggling between computational physics course or numerical analysis. They are both in graduate level (so very intensive), one in physics department and another in math. Both are taught by leading experts in scientific computing field. I have 3 plus years in computational physics research background and recently finished a parallelized research project. The reason I want to take these courses is in the past I use matlab functions, scipy library to do integration, root finding and stuff, but actually I do not really understand the inner working. So for example if i want to implement my own implicit ode algorithm , I cannot but just copy it from somewhere else and unable to develop my own to suit my specific problem. I am also not familiar with newton's method, interpolation and root finding as in numerical analysis, but very familiar with linear algebra and somewhat familiar with differentiation, integration and differential equations (I read these chapters from a numerical analysis book) . On the other hands, I am not interested in molecular dynamics or chemistry stuff, but I am interested in quantum monte carlo in condensed matter physics. Will computational physics also cover basic numerical analysis? I also want to ask: Which one do you take in the past? or did you take both? Thank you very much for your advice.