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Program checklist · Doctor of Philosophy

Doctor of Philosophy in Transportation

Massachusetts Institute of Technology · Cambridge, MA

A checklist is the list of requirements to complete this program and receive the award, as the college publishes it in its catalog. It is the same for everyone. It does not say what you have completed; that comes from applying your own record.

Program
Award
Doctor of Philosophy
Credential class
ceterms:DoctoralDegree
Total credits (published)
648-666
Catalog edition
0269
Checklist type
degree-program
Description
MIT graduate-level subjects taken to fulfill the requirements of the Master of Science in Transportation degree may be counted toward the doctoral program requirements.
Identifiers
IPEDS UNITID
166683
CourseShelf checklist
CK_166683_4aa98ae9
CollegeTransfer.Net
Institution Transfer Profile
Source
CourseShelf publish 61

Requirements to complete

Every course or condition the catalog lists, in the catalog's order.

Program Requirements

0 items

    Core Subjects

    Choose 1 of the following · Select one of the following: · major core · 8 items
    1. 1.200[J]
      Transportation: Foundations and Methods
      Not resolved to a course
      12
    2. 11.251
      Frontier of Transportation Research 1
      Not resolved to a course
      6
    3. Select one of the following:
      Not resolved to a course
      12
    4. 1.144[J]
      Applied Category Theory for Engineering Design
      Not resolved to a course
    5. 1.202
      Demand Modeling
      Not resolved to a course
    6. 1.208
      Resilient Networks
      Not resolved to a course
    7. 1.260[J]
      Logistics Systems
      Not resolved to a course
    8. 11.478
      Behavioral Science, AI, and Urban Mobility
      Not resolved to a course

    Computation/Analytics

    Choose 1 of the following · Select one of the following: · 7 items
    1. Select one of the following:
      Not resolved to a course
      6-12
    2. 6.C51& 1.C51
      Modeling with Machine Learning: from Algorithms to Applicationsand Machine Learning for Sustainable Systems 2
      Not resolved to a course
    3. 6.3732[J]
      Statistics, Computation and Applications
      Not resolved to a course
    4. 6.7900
      Machine Learning
      Not resolved to a course
    5. 6.7910[J]
      Statistical Learning Theory and Applications
      Not resolved to a course
    6. 15.071
      The AI Edge
      Not resolved to a course
    7. 15.072
      Advanced Analytics Edge
      Not resolved to a course

    Core Research Area

    major core · 1 item
    1. Select two subjects from one of the five approved areas:
      Not resolved to a course
      18-30

    Performance and Optimization

    7 items
    1. 1.208
      Resilient Networks
      Not resolved to a course
    2. 6.7220[J]
      Nonlinear Optimization
      Not resolved to a course
    3. 6.7260
      Network Science and Models
      Not resolved to a course
    4. 6.7700[J]
      Fundamentals of Probability
      Not resolved to a course
    5. 6.7720[J]
      Discrete Probability and Stochastic Processes
      Not resolved to a course
    6. 15.081[J]
      Introduction to Mathematical Programming
      Not resolved to a course
    7. 15.094[J]
      Robust Modeling, Optimization, and Computation
      Not resolved to a course

    Machine Learning and Statistics

    13 items
    1. 1.127[J]
      Reinforcement Learning: Foundations and Methods
      Not resolved to a course
    2. 6.C51& 1.C51
      Modeling with Machine Learning: from Algorithms to Applicationsand Machine Learning for Sustainable Systems 2
      Not resolved to a course
    3. 6.7250
      Optimization for Machine Learning
      Not resolved to a course
    4. 6.7730
      Modern Mathematical Statistics
      Not resolved to a course
    5. 6.7800
      Inference and Information
      Not resolved to a course
    6. 6.7810
      Algorithms for Inference
      Not resolved to a course
    7. 6.7900
      Machine Learning
      Not resolved to a course
    8. 6.7910[J]
      Statistical Learning Theory and Applications
      Not resolved to a course
    9. 6.7960
      Deep Learning
      Not resolved to a course
    10. 6.8300
      Advances in Computer Vision
      Not resolved to a course
    11. 9.521[J]
      Mathematical Statistics: a Non-Asymptotic Approach
      Not resolved to a course
    12. 9.522
      Statistical Reinforcement Learning
      Not resolved to a course
    13. 15.095
      Machine Learning Under a Modern Optimization Lens
      Not resolved to a course

    Planning and Policy 3

    3 items
    1. 11.478
      Behavioral Science, AI, and Urban Mobility
      Not resolved to a course
    2. 11.526[J]
      Comparative Land Use and Transportation Planning
      Not resolved to a course
    3. 11.540
      Urban Transportation Planning and Policy
      Not resolved to a course

    Logistics 4

    3 items
    1. 1.260[J]
      Logistics Systems
      Not resolved to a course
    2. 15.764[J]
      The Theory of Operations Management
      Not resolved to a course
    3. 15.762[J]& 15.763[J]
      Supply Chain Analyticsand Supply Chain: Capacity Analytics
      Not resolved to a course

    Demand 5

    4 items
    1. 1.202
      Demand Modeling
      Not resolved to a course
    2. 1.205
      Advanced Demand Modeling
      Not resolved to a course
    3. 14.380& 14.381
      Statistical Method in Economicsand Estimation and Inference for Linear Causal and Structural Models 5
      Not resolved to a course
    4. 14.382
      Econometrics 6
      Not resolved to a course

    Unrestricted Electives

    Select 54 units in consultation with your advisor. 54 · electives · 1 item
    1. Select 54 units in consultation with your advisor.
      Not resolved to a course
      54

    Thesis

    1 item
    1. 1.THG
      Graduate Thesis 7
      Not resolved to a course
      540
    Source. Massachusetts Institute of Technology, catalog 0269 — https://catalog.mit.edu/degree-charts/phd-transportation/. Captured page pages/0269.html.gz. Assembled from the institution's published catalog as captured; every record names its captured page and source URL. Assembled, not asserted.