Transportation Engineering 201

Description

This course has been designed for Transportation Engineers, Planners, Traffic Engineers who are absolute beginners in Data Science field. You don't need to have any background in Statistics or coding in order to take this course. In the first section, I have explained all the necessary terms related to linear regression through actual examples using data from a Parking Study. If you are not familiar with it, it is still okay as things are taught from scratch and emphasis has been given to data analysis.

Later, we discuss R programming commands to implement the same thing as taught in Section 1. I have assumed that you have a zero experience in R and hence I have explained even the most basic things.

Then, we deep dive into data analysis part and making sure that we can actually model it using linear regression. We also discuss several assumptions such as normality, linearity and constant variance of the error terms. I have shown how to check whether our model is satisfying those assumptions or not.

Lastly, we discuss models with more than one variables. I have given steps to identify suitable variables for the model.

The philosophy behind this course is to provide you with an introduction. As a Transportation Engineer, you might be curious to learn about Data Science but may not have been able to do so because of hard mathematics and coding requirements. I have broken down complex concepts and explained them here through real life applications from transportation industry to enable you to learn it.

This course helps you become strong in fundamental concepts of Linear Regression and Data Science in general. It is not very heavy in coding or mathematics.

From there onwards, we take a deep dive into Aimsun software which is used for traffic simulation. Learning this software is a skill which can be useful in the industry as well as research. I have also explained PTV VISUM basics using which 4-step modeling can be done.

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