Course Outline


  • AI for city planning

Uses and Opportunities for City Service Providers

  • Architecture, transportation, public safety, land use, environment, etc.

Applications for AI

  • Computer Vision, Natural Language Procession (NLP), Voice Recognition, etc.

The Data Behind AI

  • Data as the enabler of AI
  • Gaining access to the data

The Computation behind AI

  • Probability and Statistics as the Core
  • How Algorithms Enable Intelligence

The Logic Behind AI

  • Programming Language used in AI
  • Needed skillsets

Teaching Machines How to Learn

  •  Understanding machine learning
  • Applying machine learning libraries to develop intelligent systems

Advanced Approaches to Machine Learning

  • Deep Learning

Case Study

  • Predicting traffic bottlenecks with machine learning

The Tooling behind AI

  • Different databases for different purposes
  • Data processing engines
  • Building the infrastructure on premise or in the cloud

Analyzing the Data

  • Handling large volumes of data
  • Aggregating data across agencies
  • Data preparation, staging, analysis and reporting
  • Data mining approaches

Case Study

  • Collecting, filtering and analyzing demographic data by neighborhood

The Interplay of AI and IoT

  • Cameras, sensors, actuators, etc.
  • Assessing the city's network infrastructure

Autonomous Decision Making and Execution

  • Using rules engines and expert systems to make decisions
  • Programming machines to take actions on their own

Case Study

  • Responding to emergencies based on real-time data

Automating Human Processes

  • The interplay of humans and machine
  • Optimizing processes in municipal departments

Bringing it All Together

  • The low-hanging fruit for city planners
  • Constructing a city wide digital platform

Planning and Communicating an AI Strategy

  • Needs assessment and return on investment
  • Bringing together city leaders, agencies, businesses and universities

Summary and Conclusion


  • An understanding of city planning
  • A basic understanding of programming concepts
  14 Hours


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