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 3.5-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.

Additional course detail is provided in the sections below.

• Course Topics
  • 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 being used in transportation, and where these tools are headed next for infrastructure design.
• Course Outline

  [no information available]

• What you will learn

  Students will work hands-on with actual regional datasets to build complete analytics pipelines from start to finish. In addition, students 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.

  Students will gain practical experience with real-world mobile device data and learn how to interpret it alongside your models. Most importantly, students will learn how to translate technical findings into the kind of clear, compelling analysis that drives investment decisions and shapes policy. Students will leave with a grasp of the challenges of using machine learning and GenAI in transportation — and how to position themselves and their 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.

• Course Prerequisites

  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 to analyze.

  Background Reading & Industry Standards:

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

  Jane Macfarlane, PhD, Executive Director Smart Cities, UC Berkeley, ITS 

  Jane holds a joint appointment at the University of California at Berkeley and Lawrence Berkeley National Laboratory, where she is the Director of the Smart Cities and Sustainable Mobility Center. She has over 30 years of experience in high-performance computing, data analytics, and geospatial mapping.

  Jane has been responsible for directing industry research groups including: Head of Research for HERE — a leader in geospatial mapping, Vice President of Process Engineering at Imara — a lithium ion battery company, and Director of Advanced Technology Planning for OnStar at General Motors — the first at-scale, telematics solution. Her research focus is on semantic analytics, big data analytics and visualization, contextualization of data streams and spatially distributed computing. She holds 8 granted patents and currently has 14 patent applications, primarily in the domain of geospatial data analytics. She holds a Ph.D. in Mechanical Engineering from the University of Minnesota.

• Registration Information

  Registration for this course occurs at the TechTransfer training host site. Use the button to the right to directly access the course page and registration portal. You will be asked to create a user account as part of the registration process.

  A confirmation email will be sent to you within two business days of TechTransfer receiving your paid registration.

  If you have any questions or need assistance, please contact the TechTransfer Registrar at (510) 643-4393 or registrar@techtransfer.berkeley.edu.

• For more information

  To learn more about TechTransfer courses and credits, see their FAQ (https://www.techtransfer.berkeley.edu/faq-page).

  To learn more about TechTransfer's cancellation, refund, and substitution policies, see How to Enroll (https://www.techtransfer.berkeley.edu/enrollment/how-enroll).

  Cancellation Policy:

  The cancellation fee for this course is $75. At TechTransfer, there are no refunds for classes with registration fees of $75 or less. For all other classes, you may cancel your enrollment and receive a refund of your registration fee less $75, provided they receive your written request to cancel at least 5 full working days before the class is scheduled to begin. In lieu of canceling your registration, you may (1) transfer your registration to another TechTransfer class, (2) receive a tuition credit for the full amount, useable toward a future class, or (3) send a substitute in your place.

  Note: TechTransfer recommends 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.