Master of Engineering in Transportation Engineering
The Master of Engineering in Transportation Engineering is a coursework-only, professionally-oriented degree program that permit a concentration in preparation for engineering practice. With a Master of Engineering in Transportation Engineering degree, a student will be a qualified transportation planner, traffic engineer, and traffic safety engineer. Additionally, the student will be trained to understand and evaluate the socioeconomic impacts of transportation and infrastructure engineering projects. Up to 12 credit hours of 400-level undergraduate coursework may be included in the program with prior adviser approval. No thesis or comprehensive examination is required for completion of the degree.
Curriculum
| Code | Title | Credit Hours |
|---|---|---|
| Required Courses | (9) | |
| Select a minimum of three courses from the following with adviser consent: | 9 | |
| Statistical Analysis of Engineering Data | 3 | |
| Demand Models for Urban Transportation | 3 | |
| Urban Transportation Planning | 3 | |
| Public Transportation Systems | 3 | |
| Transportation Systems Evaluation | 3 | |
| Systems Analysis in Civil Engineering | 3 | |
| Intelligent Transportation Systems | 3 | |
| Algorithms in Transportation | 3 | |
| Elective Courses | (21) | |
| Select 21 credit hours from the following: 1 | 21 | |
| Facility Design of Transportation Systems | 3 | |
| Railroad Engineering and Design | 3 | |
| Introduction to Transportation Engineering and Design | 3 | |
| Probability Concepts in Civil Engineering Design | 3 | |
| Advanced Bridge Engineering | 3 | |
| Introduction to Geographic Information Systems | 3 | |
or CAE 439 | Introduction to Geographic Information Systems | |
| Asphalt and Concrete Mix Design | 3 | |
| Pavement Evaluation and Management | 3 | |
| Traffic Operations and Flow Theory | 3 | |
| Advanced Traffic Engineering | 3 | |
| Transportation Systems Management | 3 | |
| Transportation Economics, Development and Policy | 3 | |
| Transportation Asset Management | 3 | |
| Economic Decision Analysis in Civil Engineering | 3 | |
| Special Problems | 0-3 | |
| Probability and Statistics | 3 | |
| Design and Analysis of Experiments | 3 | |
| Mathematical Modeling | 3 | |
| Statistical Models and Methods | 3 | |
| Stochastic Processes | 3 | |
| Mathematical Statistics | 3 | |
| Regression | 3 | |
| Monte Carlo Methods | 3 | |
| Advanced Design of Experiments | 3 | |
| Data Preparation and Analysis | 3 | |
| Bayesian Computational Statistics | 3 | |
Minimum degree credits required: 30
- 1
If more than three courses from the required courses list are taken, those additional courses can be applied as electives
Up to 12 credit hours of 400-level courses can be applied to the program.
A maximum of 3 credit hours of 597 Special Problems can be applied to the degree program.
Specialization in Artificial Intelligence
| Code | Title | Credit Hours |
|---|---|---|
| Required Courses | (9) | |
| Select a minimum of 9 credit hours from the following with adviser consent: | 9 | |
| Statistical Analysis of Engineering Data | 3 | |
| Demand Models for Urban Transportation | 3 | |
| Urban Transportation Planning | 3 | |
| Public Transportation Systems | 3 | |
| Transportation Systems Evaluation | 3 | |
| Systems Analysis in Civil Engineering | 3 | |
| Intelligent Transportation Systems | 3 | |
| Algorithms in Transportation | 3 | |
| AI Course Requirements | (9) | |
| Select 9 credit hours from the following: | 9 | |
| Data Mining | 3 | |
| Introduction to Algorithms | 3 | |
| Advanced Data Mining | 3 | |
| Combinatorial Optimization | 3 | |
| Game Theory: Algorithms and Applications | 3 | |
| Deep Learning | 3 | |
| Interactive and Transparent Machine Learning | 3 | |
| Topics in Machine Learning | 3 | |
| Machine Learning | 3 | |
| Artificial Intelligence and Edge Computing | 3 | |
| Machine and Deep Learning | 3 | |
| Object-Oriented Programming and Machine Learning | 3 | |
| Elective Courses | (12) | |
| Select 12 credit hours from the following: 1 | 12 | |
| Facility Design of Transportation Systems | 3 | |
| Railroad Engineering and Design | 3 | |
| Introduction to Transportation Engineering and Design | 3 | |
| Probability Concepts in Civil Engineering Design | 3 | |
| Advanced Bridge Engineering | 3 | |
| Introduction to Geographic Information Systems | 3 | |
or CAE 439 | Introduction to Geographic Information Systems | |
| Asphalt and Concrete Mix Design | 3 | |
| Pavement Evaluation and Management | 3 | |
| Traffic Operations and Flow Theory | 3 | |
| Advanced Traffic Engineering | 3 | |
| Transportation Systems Management | 3 | |
| Transportation Economics, Development and Policy | 3 | |
| Transportation Asset Management | 3 | |
| Economic Decision Analysis in Civil Engineering | 3 | |
| Special Problems | 0-3 | |
| Probability and Statistics | 3 | |
| Design and Analysis of Experiments | 3 | |
| Mathematical Modeling | 3 | |
| Statistical Models and Methods | 3 | |
| Stochastic Processes | 3 | |
| Mathematical Statistics | 3 | |
| Regression | 3 | |
| Monte Carlo Methods | 3 | |
| Advanced Design of Experiments | 3 | |
| Data Preparation and Analysis | 3 | |
| Bayesian Computational Statistics | 3 | |
Minimum degree credits required: 30
- 1
If more than three courses from the required courses list are taken, those additional courses can be applied as electives
Up to 12 credit hours of 400-level courses can be applied to the program.
A maximum of 3 credit hours of 597 Special Problems can be applied to the degree program.
