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Resilience Planning for Coastal Hazards
Across the world, sea levels are rising and storm surge events are intensifying, while development is increasing in vulnerable coastal areas and groundwater depletion is causing land to sink. Urban planners are uniquely positioned to join the battle against rising seas.
Introduction to GIS, Part 2
Take the next step into the world of Geographic Information Systems (GIS) and ArcGIS Pro with an overview of navigation, map projections, and essential map design principles.
Navigating the Ethical Landscape for AI in Urban Planning
Uncover some of the largest ethical issues related to using AI in urban planning and the steps cities around the world are taking to ensure fairness, honesty, and accountability as this revolutionary technology becomes more embedded in the modern world.
Demystifying AI: Terminology, Tools, and Techniques for Urban Planners
Understanding the basics of artificial intelligence, or AI, is increasingly important for urban planners. Learn the capabilities, limitations, and language of emerging technologies that utilize AI methods.
Crime and Urban Planning in the United States
The spatial patterns and environmental characteristics of urban crime offer planners an opportunity to contribute to building crime-resilient communities.
Resilience Planning for Floods
This course builds on the "Introduction to Resilience Planning" course and uses the approach presented there as the framework for addressing flood threats in communities.
Introduction to Smart Cities
This course explores the characteristics and the challenges of smart cities, as well as the potential opportunities for a smart cities approach within the urban design and urban planning fields. This course also discusses the drivers and the essential technologies in a smart city.
Measuring Neighborhood Segregation and Diversity
This course reviews the various ways to measure both segregation and diversity at the neighborhood scale.
Coding for Planners: Up and Running with Python
Python is one of the world’s most popular programming languages, particularly among beginners, thanks to its clear and straightforward syntax. It is also one of the most widely used languages for data science.