With the rapid advancements in artificial intelligence (AI) and its transformative impact across industries, roadway professionals are uniquely positioned to benefit from the integration of AI into transportation infrastructure, highway operations, and management. This course is designed to provide participants with a foundational understanding of AI concepts and their practical applications in roadway engineering and operations.

This online training emphasizes AI-driven tools and techniques that enhance decision-making, optimize operations, and provide actionable insights for transportation professionals. No prior experience with coding or computer programming is required, making the course accessible to a broad audience of road professionals.

The program covers key topics, alongside an introduction to data science principles such as data processing, visualization, and mining. Through interactive modules and practical tutorials, participants will acquire the skills needed to leverage AI-powered tools using real-world transportation datasets.

This course will empower highway practitioners, roadway professionals, and local agency engineers to harness AI’s potential to enhance roadway planning, construction, and management.

Why Online?

• Earn 16 IRF Professional Development Hours
• Expert training by professionals for Professionals: access IRF’s unique curriculum and lectures developed by world-class specialists
• Accelerated learning processes: get up to speed and gain new insights in less time and with no travel constraints
• Full access to learning materials and session recordings
• Small classrooms & scheduled One-on-One sessions with instructors
• Self-paced options available
• Interactive group projects and case studies
• Receive IRF Certification

Format

Lectures will be taught over a four-week period with live 2-hour online sessions held Monday – Thursday each week. Upon completion of the training program, the IRF will administer an online knowledge test. Participants with a score of 80% at the exam will be awarded a certificate verifying the successful completion of the course.

Learning Objectives

• Understand fundamental AI concepts and their relevance to roadway and transportation applications.
• Explore practical applications of AI for highway agencies and local authorities.
• Gain familiarity with data visualization, mining, and processing tools tailored to transportation needs.
• Learn about emerging AI trends in roadway engineering, operations, and maintenance.
• Develop practical skills to implement and utilize AI methods for managing and analyzing transportation data.

Target Audience

• Local and Rural Road Authorities
• Executive Highway and Transportation Engineers
• Road/Highway Design Engineers and Consultants
• Transportation Infrastructure Contractors
• Road/Highway Authorities & Operators
• Materials and QC/QA Engineers
• Transportation Infrastructure Practitioners

Upon completion of the training program, the IRF will administer an online knowledge test. Participants with a score of 80% at the exam will be awarded a certificate verifying the successful completion of the course.

Lectures will be taught over a four-week period with live 2-hour online sessions held Monday – Thursday each week.  Monday – Thursday (8:00 AM – 10:00 AM EST)

LEAD INSTRUCTOR

Mehran Mazari, Ph.D.
Assistant Professor, California State University Los Angeles

Dr. Mehran Mazari is an Assistant Professor in the Department of Civil Engineering at Cal State LA, specializing in Transportation Infrastructure, Materials and Applied Data Science, Artificial Intelligence (AI) and Machine Learning (ML). He is the faculty director of Sikand Center for Sustainable and Intelligent Infrastructures (SITI-Center) and founder of Sustainable Infrastructure Materials Research Lab (SIM-Lab) at Cal State LA. His research interests include sustainable and resilient transportation infrastructure, transportation infrastructure materials, and non-destructive evaluation of transportation infrastructure. He is member of technical committees at the Transportation Research Board of National Academies of Science and Engineering and co-chair of the LTPP subcommittee of the Highway Pavement Committee of the American Society of Civil Engineers (ASCE). Dr. Mazari has published more than 60 peer-reviewed journal and conference papers. He has been actively involved in several national and state research projects, including the National Highway Cooperative Research Program (NCHRP) and Federal Highway Administration (FHWA), among others.

Operating System
Windows 7 – Windows 10, Mac OS X 10.9 (Mavericks), macOS Catalina (10.15), Linux, Google Chrome OS, Android OS 5 (Lollipop) – Android 9 (Pie), iOS 10 – iOS 12, Windows Phone 8+, Windows 8RT+

Web browser
Google Chrome (most recent 2 versions)
Mozilla Firefox (most recent 2 versions)
Internet Explorer v11 (with Adobe Flash if running Windows 7)
Apple Safari (most recent 2 versions)
Microsoft Edge (most recent 2 versions)

Internet connection
1 Mbps or better (broadband recommended)

Hardware
2GB of RAM (minimum), 4GB or more of RAM (recommended)
Microphone and speakers (USB headset recommended)

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