This class is offered in partnership with the California Department of Transportation, Division of Local Assistance. Registration fees are subsidized with funding from the Cooperative Training Assistance Program. Reduced rates are available to employees of California's city, county, regional, and other public agencies only.

Credits

This course grants 2.4 CEUs and 24 AICP CM credits. (Pending AICP Approval)

Description

The decisions you make every day - where to invest infrastructure dollars, how to respond to incidents, how to plan for future growth - are only getting more complex. This three-and-a-half-day, hands-on course gives you practical tools to make those decisions with greater confidence and clarity. Using KNIME, a visual, low-code platform, you will learn about real analytics pipelines with actual regional datasets - no programming experience needed. You will leave with a working understanding of how geospatial data, AI, and simulation can strengthen the work you are already doing: designing EV charging networks, building resilient evacuation strategies, and understanding the environmental impacts of road decisions.

Click here for a detailed outline.

Topics Include

• Data Science Pyramid: See how raw data flows through each stage to become meaningful insights that support real decisions.
• Geospatial-Temporal Data Analytics: Work with mobile device data to understand how people and goods actually move through your region - and what that means for planning and operations.
• Enterprise Ontologies: Build the data foundation your organization needs - a shared language for your business processes that makes data consistent, reusable, and actionable.
• Synthetic Population Modeling: Understand how synthetic populations are growing into rich activity models used to model travel demand - bringing a new level of realism to transportation forecasting.
• Infrastructure Design Use Cases: Apply data-driven methods to real-world challenges: siting EV charging infrastructure and designing evacuation routes that consider human behavior in an event.
• Applied AI/ML: Explore how machine learning and generative AI are already being used in transportation - and where these tools are headed next for infrastructure design.

What You Will Learn

You will work hands-on with actual regional datasets to build complete analytics pipelines from start to finish. You will see how synthetic populations are generated and used to simulate activity at scale - including a full simulation of the Bay Area across 101 cities. You will gain practical experience with real-world mobile device data and learn how to interpret it alongside your models. Most importantly, you will learn how to translate technical findings into the kind of clear, compelling analysis that drives investment decisions and shapes policy. You will leave with a grasp of the challenges of using machine learning and GenAI in transportation - and how to position yourself and your organization for what is coming.

Who Should Attend

This course is built for mid-career professionals in DOTs, cities, and consulting firms - Traffic Engineers, Urban Planners, GIS Analysts, Data Architects, and Smart City leads - who are ready to bring data-driven thinking into their day-to-day work. If you are managing transportation models, leading a digital transformation effort, or simply looking for better ways to support the decisions your organization needs to make, this course is for you. You don't need to be a data scientist. You just need to be curious about what's possible.

Class Technical Information

All attendees are required to bring their own laptop. You can install KNIME directly on your laptop before class or simply log in through a browser-based virtual desktop that has everything pre-configured. Either way, you will be ready to work from day one. Sessions are structured around small groups, so you can engage at whatever level feels comfortable - whether you want to dive in and build or focus on understanding the concepts and outcomes. All participants are encouraged to bring a small data problem you are interested in analyzing.

Background Reading and Industry Standards

• NCHRP 23-27 Data Ontologies for Data-Driven Decision-Making: Research Approach and Findings 2026, Research Report 1169.
• KNIME Beginner's Luck.
• www.smartcities.berkeley.edu.

For More Information

About our courses and credits, see our FAQ
About payments, refunds, confirmations, and accessibility, see How to Enroll
Or email us with your questions at registrar@techtransfer.berkeley.edu

Cancellation Policy

To cancel your registration and receive a refund less a $75 processing fee, you must notify TechTransfer at least five (5) working days before the course is scheduled to begin. Notifications must be made in writing and sent by email to registrar@techtransfer.berkeley.edu. We reserve the right to charge the full course fee if proper notification is not sent to TechTransfer. We don't offer refunds for classes with registration fees of $75 or less.

In lieu of canceling your registration, you have three additional options: you may (1) transfer your registration to another class, (2) receive a tuition credit for the total amount, useable toward a future class, or (3) send a substitute in your place. Please contact us at least 5 full working days before the class is scheduled to begin so we may process your request.

If you’ve registered for a self-paced class, you cannot receive a refund once you start the class.

We recommend you discuss any possible problems or online security issues with your IT person before you register for any online classes. If you are worried about connectivity issues, please contact the online training coordinator the week before the class to schedule a time to test your system. If you do not test your system and you have technical issues during a live online class, we will not provide a refund.

Class Technical Information:

All attendees are required to bring their own laptop. You can install KNIME directly on your laptop before class or simply log in through a browser-based virtual desktop that has everything pre-configured. Either way, you will be ready to work from day one. Sessions are structured around small groups, so you can engage at whatever level feels comfortable - whether you want to dive in and build or focus on understanding the concepts and outcomes. All participants are encouraged to bring a small data problem you are interested in analyzing.