The School requires each student to take 20 graduate-level courses.
Required Courses First Year
1. Foundations of Optimization
2. Foundations of Stochastic Modeling
3. Optimization I/Linear Programming (IEOR)
4. Stochastic Modeling I (IEOR)
5. Stochastic Modeling II (IEOR)
In addition, students must demonstrate proficiency in the area of real analysis at the level of Rudin, “Principles of Mathematical Analysis”, on the basis of prior coursework, an exemption exam, or by taking the “Introduction into Modern Analysis – I” at Columbia.
By the End of the Third Year
6. A graduate level course in game theory (e.g. “Micro II” offered by the Department of Economics or an equivalent course).
7. A graduate level course on statistical inference theory (either “Statistical Inference Theory I” offered by the Department of Statistics or “Econometrics I” offered by the Finance and Economics Division).
8. A graduate level course on advanced deterministic optimization (e.g., “Optimization II/Network Flows”, or “Integer Programming”, or “Combinatorial Optimization” offered by the IEOR Department).
9. A graduate level course in dynamic programming.
Highly Recommended Courses
graduate level course in microeconomic theory (e.g., “Micro I” offered by the
Department of Economics)
2. “Probability I” course offered by the Statistics Department.
Elective Courses1. Revenue Management.
2. Logistics and Distribution.
3. Inventory Management.
4. Supply Chain Management.
5. Competition and Coordination in Supply Chains.
7. Computing for Business Research.
8. Game-Theoretical Models in Operations.
9. Marketing Models.
10. Experimental Design and Analysis.
11. Finance Theory.
12. Computational Finance.
13. Stochastic Differential Equations.