This course is developed with the aim of preparing graduate students to obtain fundamental understanding on the data science concepts and practical skills in Python programming for analyzing databases in disciplines such as civil, mechanical, electrical, computer, and manufacturing engineering. The course covers the topics listed below. The main assessment is a final term paper where the students are asked to pick any dataset (preferably from their own research) and apply one or multiple techniques covered in the course.
Applied mathematics (linear algebra)
Probability and information theory
Machine learning basics
Introduction to Python programming
Regression analysis
Classification algorithms: Clustering analysis; K-nearest neighbor; Decision tree & ensemble learning; Principal component analysis; Support vector machine
Neural networks & deep learning
Theory and practice in transportation decision-making, planning, and modeling; advanced concepts of the transportation mathematical modeling: optimization and statistics; comprehensive presentation of trip-based models for transportation demand analysis and forecast; trip generation models; trip distribution models; trip mode choice and discrete choice models; trip assignment and network modeling; introduction to tour- and activity- based models for transportation demand analysis.
In this course, students gain knowledge on basic concepts and theories of transportation engineering and planning, and mathematics behind them as well as their applications on the real-world examples. By the end of the semester, students learn how to approach a transportation-related problem by identifying the problem, selecting the appropriate method, collecting the required database, analyzing the database by applying the method, and then draw conclusions in the form of analyzing the possible scenarios and suggesting the best one.
This course focuses on the theory and practice in highway design; advanced concepts of the design of streets and highways; highway functional classification and design criteria; location studies; advanced concepts of the design of vertical and horizontal alignment; intersections and highway drainage elements design criteria; highway cross section design and earthwork volume; theory and practice in pavement design; characterization of pavement layer materials; introduction to pavement management systems.