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Course Outline

Introduction

  • Applying AI to urban planning

Opportunities and Applications for City Service Providers

  • Sectors such as architecture, transportation, public safety, land use, and environmental management.

AI Application Domains

  • Computer Vision, Natural Language Processing (NLP), Voice Recognition, among others.

The Data Foundation of AI

  • Recognizing data as the critical enabler of AI capabilities.
  • Strategies for accessing relevant data sources.

The Computational Core of AI

  • Probability and statistics as foundational elements.
  • Understanding how algorithms facilitate intelligent behavior.

The Logical Framework of AI

  • Programming languages commonly utilized in AI development.
  • Essential skills and competencies required.

Educating Machines: The Path to Learning

  • Grasping the principles of machine learning.
  • Utilizing machine learning libraries to build intelligent systems.

Advanced Machine Learning Methodologies

  • Deep Learning techniques.

Case Study

  • Predicting traffic congestion points using machine learning algorithms.

AI Infrastructure and Tooling

  • Selecting appropriate databases for specific use cases.
  • Data processing engines.
  • Establishing infrastructure either on-premise or via cloud solutions.

Data Analysis Techniques

  • Managing and processing large datasets.
  • Integrating data across various municipal agencies.
  • Data preparation, staging, analysis, and reporting workflows.
  • Data mining strategies and approaches.

Case Study

  • Gathering, filtering, and analyzing demographic data by neighborhood.

The Intersection of AI and IoT (Internet of Things)

  • Utilizing cameras, sensors, actuators, and other devices.
  • Evaluating the city's network infrastructure.

Autonomous Decision-Making and Execution

  • Employing rule engines and expert systems for decision support.
  • Programming systems to act autonomously.

Case Study

  • Real-time emergency response mechanisms based on live data feeds.

Automating Human-Centric Processes

  • The synergy between human operators and machines.
  • Optimizing operational workflows within municipal departments.

Integrating Concepts: Bringing it All Together

  • Identifying quick wins and low-hanging fruit for city planners.
  • Designing a comprehensive city-wide digital platform.

Strategic Planning and Communication for AI Adoption

  • Conducting needs assessments and calculating return on investment.
  • Collaborating city leadership, agencies, private businesses, and academic institutions.

Summary and Conclusion

Requirements

  • Fundamental knowledge of urban planning principles
  • A foundational understanding of programming concepts
 14 Hours

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