Courses for a One Year Master's in Transportation Engineering

The One-year Master’s in Transportation Engineering (1MS) equips students with advanced knowledge in the fundamentals of transportation analysis and design. The program requires completion of 30 credits including technical courses (25 cr), a one-credit seminar, and an internship (4 cr). The technical courses can be completed in two full-time semesters.

Category 1: Fundamental Courses (9 credits)

All required, these courses focus on the methods used in transportation engineering

CEGE 5214: Infrastructure Systems Engineering (3 cr)
CEGE 5218: Methods for Intelligent Transportation Systems (3 cr)
STAT 5021: Statistical Analysis (3 cr) or equivalent

Category 2: Transportation Technical Courses (9 credits)

Minimum 3 courses, these courses focus on different aspects of transportation systems

CEGE 4253: Pavement Design, Engineering, and Management (4 cr)
CEGE 5211: Highway Design and Traffic Operations (4 cr)
CEGE 5213: Transit Planning and Management (3 cr)
CEGE 5219: Air Transportation Systems (3 cr)

Category 3: Advanced Transportation Courses (3 credits)

Minimum 1 course, these courses address advanced methods in transportation engineering

CEGE 8211 Theory of Traffic Flow (3 cr)
CEGE 8215 Transportation Data Analysis (3 cr)
CEGE 8217 Transportation Network Analysis (4 cr)
Other advanced courses offered occasionally
If none is offered, an alternative course will be selected in consultation with adviser

Category 4: Cross-disciplinary Knowledge (4 credits)

Additional course to meet the required credits. Sample courses are listed in the appendix. Remaining courses from Categories 1–3 may be taken. Other, not-listed courses may be taken with adviser’s approval.

Seminar (1 credit)

Minimum 1 course, these courses address the topics in transportation research and technology

CEGE 8200: Transportation Seminar (1 cr)
CEGE 8213: Advanced Transportation Technologies Seminar (1 cr)

Internship (4 credits)

CEGE 5196: Industrial Internship in Civil Engineering (4 cr)

Appendix: Sample Cross-disciplinary Courses

Popular courses for transportation engineering graduate students are usually found in the following departments: Statistics, Industrial and Systems Engineering, Electrical and Computer Engineering, Computer Science and Engineering, Geography, Urban Planning, etc.

AEM 8423: Convex Optimization Methods in Control (3 cr)
CSCI 4521: Applied Machine Learning for Computer and Data Scientists (3 cr)
CSCI 5511: Artificial Intelligence I (3 cr)
CSCI 5512: Artificial Intelligence II (3 cr)
CSCI 5523: Introduction to Data Mining (3 cr)
CSCI 5525: Machine Learning: Analysis and Methods (3 cr)
CSCI 5527: Deep Learning: Models, Computation, and Applications (3 cr)
CSCI 5715: From GPS, Google Maps, and Uber to Spatial Data Science (3 cr)
EE 4231: Linear Control Systems: Designed by Input/Output Methods (3 cr)
EE 4233: State Space Control System Design (3 cr)
EE 4235: Linear Control Systems Laboratory (1 cr)
EE 4237: State Space Control Laboratory (1 cr)
EE 5231: Linear Systems and Control (3 cr)
EE 5235: Robust Control System Design (3 cr)
EE 5239: Intro to Nonlinear Optimization with Applications in Machine Learning and Artificial Intelligence (3 cr)
EE 5241: Optimal Control and Reinforcement Learning (3 cr)
EE 5251: Optimal Filtering & Estimation (3 cr)
EE 5389: Introduction to Predictive Learning (3 cr)
EE 5521: Intro to Machine Learning and Data Science for Electrical and Computer Engineers & Roboticists (3 cr)
EE 5531: Probability and Stochastic Processes (3 cr)
EE 5571: Statistical Learning and Inference (3 cr)
EE 8215: Nonlinear Systems (3 cr)
EE 8231: Optimization Theory (3 cr)
GEOG 5564: Urban GIS and Analysis (3 cr)
IE 5012: Discrete Optimization Methods and Applications (4 cr)
IE 5285: Engineering the Allocation of Public Resources (4 cr)
IE 5532: Stochastic Models (4 cr)
IE 5533: Operations Research for Data Science (3 cr)
IE 5545: Decision Analysis (4 cr)
IE 5553: Simulation (4 cr)
IE 5561: Analytics and Data-Driven Decision Making (4 cr)
IE 8521: Optimization (4 cr)
IE 8531: Discrete Optimization (4 cr)
IE 8532: Stochastic Processing & Queueing Systems (4 cr)
IE 8533: Advanced Stochastic Processes and Queuing Systems (4 cr)
IE 8554: Advanced Production and Inventory Systems (4 cr)
IE 8564: Optimization for Machine Learning (4 cr)
ME 8281: Advanced Control System Design I (3 cr)
PA 5233: Sustainable Transportation (3 cr)
PA 5234: Urban Transportation Planning and Policy (3 cr)
PUBH 7430: Statistical Methods for Correlated Data (3 cr)
PUBH 7440: Introduction to Bayesian Analysis (3 cr)
PUBH 7475: Statistical Learning & Data Mining (3 cr)
STAT 4051: Statistical Machine Learning I (4 cr)
STAT 4052: Statistical Machine Learning II (4 cr)
STAT 5021: Statistical Analysis (4 cr)
STAT 5052: Statistical and Machine Learning (3 cr)
STAT 5101: Theory of Statistics I (4 cr)
STAT 5102: Theory of Statistics II (4 cr)
STAT 5302: Applied Regression Analysis (4 cr)
STAT 8051: Advanced Regression Techniques: linear, nonlinear and nonparametric methods (4 cr)
STAT 8053: Applied Statistical Methods 3: Multivariate Analysis and Advanced Regression (3 cr)
STAT 8056: Advanced Topics on Machine Learning (3 cr)
STAT 8105: Generative Artificial Intelligence: Principles and Practices
STAT 8311: Linear Models (3 cr)
STAT 8312: Linear and Nonlinear Regression (3 cr)

1YMS Overview 1MS Internship Experience

For further information

Contact
Dr. Ebrahim Shemshadian
Director of the One-Year Master’s Program in Structural Engineering
[email protected]