The following list indicates courses frequently taken by Operations Research Center students pursuing a doctoral degree in operations research.
In addition to strictly OR-related course areas (e.g., optimization techniques, probabilistic modeling), students often take courses in applied mathematics, in disciplines closely related to operations research (e.g., statistics, computer science, finance, economics), and in various application areas (e.g., urban service systems, management science, manufacturing, transportation systems).
For more information on the courses, visit the MIT Subject Listing & Schedule, Stellar Course Guide, or MIT Open Courseware pages.
A list of courses that can be used to satisfy the PhD core program requirements
Analytics
- 15.072 – The Analytics Edge
Statistics and Machine Learning
- 6.7900 – Machine Learning
- 6.7910J/9.520J – Statistical Learning Theory and Applications
- 6.7940 – Dynamic Programming and Reinforcement Learning
- 6.7960 – Deep Learning
- 6.8300 – Advances in Computer Vision
- 6.8610 – Quantitative Methods for Natural Language Processing
- 6.S951 – Modern Mathematical Statistics
- 15.068 – Statistical Consulting
- 15.077 – Statistical Theory and Data Mining
- 15.095 – Machine Learning Under a Modern Optimization Lens
- 18.100B – Real Analysis
- 18.175 – Theory of Probability
- 18.338 – Eigenvalues of Random Matrices
- 18.443 – Statistics for Applications
- 18.445 – Introduction to Stochastic Processes
- 18.657 – Topics in Statistics
- 18.676 – Stochastic Calculus
Operations Management
- 2.852 – Manufacturing Systems Analysis
- 15.760 – Introduction to Operations Management
- 15.761 – Operations Management
- 15.762 – Supply Chain Planning
- 15.764.1 – Inventory Theory and Supply Chains
- 15.764.2 – Revenue Management and Pricing
- 15.777 – Introduction to Healthcare Delivery in the United States
Optimization
- 6.7210J/15.081J – Introduction to Mathematical Programming
- 6.7220J/15.084J – Nonlinear Optimization
- 6.7230 – Algebraic Techniques and Semidefinite Optimization
- 6.7940 – Dynamic Programming and Stochastic Control
- 6.854J/18.415J – Advanced Algorithms
- 15.082J/ESD.78J – Network Optimization
- 15.083 – Integer Optimization
- 15.094J/1.142J – Robust Modeling, Optimization, and Computation
- 15.099 – Special Seminar in Operations Research
- 18.314 – Combinatorial Analysis
- 18.315 – Combinatorial Theory
Economics and Finance
- 14.381 – Statistical Methods in Econometrics
- 14.382 – Econometrics
- 14.416J/15.416J Introduction to Financial Economics
- 14.440J/15.440J Advanced Financial Economics I
- 14.442J/15.442J Advanced Financial Economics III
- 14.74 – Foundations of Development Policy
- 15.012 – Applied Macro- and International Economics
- 15.450 – Analytics of Finance
- 15.460 – Applied Quantitative Finance
Transportation Systems
- 1.202J/ESD.212J – Demand Modeling
- 1.207 Computer Algorithms in Systems Engineering
- 1.233J/16.763J Air Transportation Operations Research
- 1.260J/15.770J – Logistics Systems
- 16.72 – Air Traffic Control
- 16.781J/1.231J – Planning and Design of Airport Systems
Applied Operations Research
- 1.203J/6.281J/11.526J/13.665J/15.073J/16.76J – Applied Probability and Stochastic Models
- 15.072 – The Analytical Edge
- 15.777 – Introduction to Healthcare Delivery in the United States
- 15.768 – Management Services: Concepts, Design, and Delivery
- 15.S09 – Energy Systems Optimization
- 16.888J/ESD.77J – Multidisciplinary System Design Optimization
Probabilistic Modeling
- 2.997 – Advanced Topics in Mechanical Engineering
- 6.3702 – Introduction to Probability
- 6.7700J/15.085J – Fundamentals of Probability (previously offered as 6.975)
- 6.7710 – Discrete Stochastic Processes
- 6.7720J/15.070J – Discrete Probability and Stochastic Processes
- 15.098 – Special Seminar in Applied Probability and Stochastic Processes
- 18.440 – Probability and Random Variables