I'm currently a 2nd-year MS student in Mathematics at a mediocre state school. I'm planning to apply for the PHD programs in Operation Research/Financial Mathematics at schools like Columbia, Cornell, CMU, Georgia Tech, etc. I got straight As in Fourier Analysis (written by Elias Stein) and Linear Programming (written by I. Griva and A. Sofer) classes last year. For the incoming Fall semester, I currently consider taking 1 course out of the following, but not sure which one would benefit me the most for getting into one of the programs above:
Nonlinear Programming - Linear and Nonlinear Optimization by A. Sofer and I. Griva
Stochastic Processes - Introduction to Probability Models by Sheldon Cross
Complex Analysis - Banach spaces of Analytic Functions by Keneth Hoffman
Probability Theory - Probability by Alan Karr
I'm thinking of taking either $1$ or $3$, but I also saw that Stochastic Processes and Nonlinear Programming are core courses for the ORIE/ORFE programs at Columbia, Cornell, CMU, Georgia Tech, etc. Thus I am not entirely sure which one I should take to be well-prepared for such programs. Can anyone please give me some advice on which one of these $4$ courses should I absolutely need to take?