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Technical Courses for Grad School in Operations Research

CountOfMonteCCountOfMonteC Registered User Posts: 14 New Member

I'm a sophomore studying Financial Engineering. My goal is to continue on to graduate school in Operations Research. I realize the biggest aspects of my application will be research experience and letters of recommendation, but I want to make sure I will have the necessary technical background to do serious research in the field (I'm leaning towards research in Stochastic Analysis, but it's a little early to limit research interests). Here are the math/stat/cs classes I've taken or plan to take:

Math Classes
-Calc 1 & 2,
-Honors Multivariable Calc
-Honors Differential Equations
-Intro to Linear Algebra
-Methods of Proof
-Probability Theory (upper level - calc based)
-Real Analysis 1 & 2
-Numerical Solutions in Linear Algebra and Optimization
-and either a course in Stochastic Processes or Measure Theory (both are grad level)

Stat Classes
-Probability & Statistics for Engineers
-Regression and Multivariate Analysis
-Econometrics (econ capstone course)
-Financial Econometrics
-two courses in Financial Engineering that are rather stat heavy

CS Classes
-Intro to Programming (Java)
-two courses in Data Structures and Algorithms
-Artificial Intelligence
-Machine Learning
-I also plan to self study C++ and hopefully cary out a project or two with that language

I'll also take several IE courses (including two courses in Operations Research) and enough economics courses to almost have an econ minor. Does this seem like a strong background for Phd programs in Operations Research? Any essential courses I'm missing?

Replies to: Technical Courses for Grad School in Operations Research

  • ucbalumnusucbalumnus Registered User Posts: 72,187 Senior Member
    Try looking up some operations research PhD programs to see if they have lists of expected undergraduate course work to prepare for the PhD programs. If such lists are not available, look for the course work for first year PhD students in the catalog, then look at the undergraduate-level prerequisites for those courses. These prerequisites would be the more important undergraduate courses that you need to be prepared for PhD study without having to take "catch up" course work.

    For example, the PhD program in IEOR at Berkeley has the following course requirements:
    Note that advanced undergraduate math courses in real analysis and linear algebra are specifically stated as required. Looking through the course catalog at:
    shows that many of the courses have undergraduate prerequisites in probability theory, statistics, operations research, or linear programming.

    You can to a similar inspection of the course work and prerequisite requirements for other schools.
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