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AI for Transportation: From Concepts to Implementation

Learn how AI is helping cities move people more safely, efficiently, and fairly—from understanding travel behavior to building smarter, more responsive mobility systems.

AI for Transportation: From Concepts to Implementation

Learn how AI is helping cities move people more safely, efficiently, and fairly—from understanding travel behavior to building smarter, more responsive mobility systems.

Discover how artificial intelligence (AI) is reshaping the way cities think about transportation. In this course, you'll start with the basics—how urban mobility systems are built, why problems like congestion, safety, and inequality are so hard to solve, and why technology alone isn't enough. From there, you'll explore how researchers model the choices people make when they travel, moving from classic economic theories to modern machine learning approaches.

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You'll then look at how AI actually gets used in the real world—such as predicting crowding on platforms, improving bus schedules, and analyzing rider feedback—and learn why success depends just as much on data quality and human judgment as it does on the algorithm itself.

AI for Transportation: From Concept to Implementation is one of the industry-specific courses in Universal AI, a self-paced program designed to help you go from beginner to AI authority—no coding or technical skills required.

What you'll learn

  • Identify the key parts of an urban transportation system and explain how human behavior, technology, and policy all shape how well it works
  • Compare older travel behavior models with modern machine learning approaches, and understand when combining both gives better results
  • Evaluate real AI deployments in transportation and understand what makes them succeed or fail outside of controlled settings
  • Understand the difference between AI models that make predictions and those that generate new data, and see how both are useful in planning
  • Apply a people-centered, problem-first approach to evaluating whether an AI tool is practical, transparent, and actually useful in a real transportation context

Meet your instructors

  • Featured image for Jinhua Zhao
    Professor of Cities and Transportation

    Jinhua Zhao is the Class 1941 Professor of Cities and Transportation at the Massachusetts Institute of Technology (MIT). Prof. Zhao integrates behavioral and computational thinking to decarbonize the world’s mobility system. Prof. Zhao founded the MIT Mobility Initiative, coalescing the Institute’s efforts on transportation research, education, entrepreneurship, and engagement. He hosts the MIT Mobility Forum, highlighting transportation innovation from MIT and across the globe. 

    Prof. Zhao directs the JTL Urban Mobility Lab and Transit Lab, leading long-term collaborations with transportation authorities and operators worldwide and enabling cross-culture learning between cities in North America, Asia and Europe. 

    Prof. Zhao leads the program “Mens, Manus and Machina (M3S): How AI Impacts the Future of Work and Future of Learning” at the Singapore MIT Alliance for Research and Technology (SMART).

Who can take this course?

Because of U.S. Office of Foreign Assets Control (OFAC) restrictions and other U.S. federal regulations, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba, North Korea and the Crimea, Donetsk People's Republic and Luhansk People's Republic regions of Ukraine.