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Courses/Architecture/Urbanism

Urban Analytics & Computational Design for Architects

Master data-driven spatial analysis and algorithmic tools to optimize urban planning, build sustainable cities, and elevate your architectural practice.

Created byMahmud Tantoush
BeginnerUpdated Jul 14, 2026
Urban Analytics & Computational Design for Architects

What You'll Learn

check_circleExplain how urban analytics and computational design methods are applied in contemporary urban and architectural practice
check_circleAnalyse spatial and behavioural data to identify patterns in movement, density, and land use
check_circleApply principles of complexity theory to understand cities as dynamic, interconnected systems
check_circleTranslate computational and data-driven insights into informed urban design strategies

About This Course

Cities are no longer static compositions—they are living, evolving systems shaped by flows of people, infrastructure, data, and environment. As urban environments become increasingly complex and data-rich, architects and urban designers are turning to computational methods to better understand and shape the forces that define them.

This session introduces urban analytics and computational design as powerful tools for evidence-based urban and architectural decision-making. Participants will explore how spatial data, digital modelling, and computational workflows can uncover hidden patterns in movement, density, land use, and social behaviour. Framed through the lens of complexity theory, the session demonstrates how cities can be understood as dynamic systems—enabling more adaptive, resilient, and responsive design strategies for the built environment.

Key Topics Discussed:

  • Urban systems as complex, dynamic networks
  • Introduction to urban analytics in architectural and urban design practice
  • Computational design methods for evidence-based decision-making
  • Spatial data analysis: movement, density, and land use patterns
  • Urban morphology and spatial configuration analysis
  • Digital modelling workflows for urban environments
  • Data sources for urban analysis (GIS, sensor data, mobility data, etc.)
  • Complexity theory and its application to urban systems
  • Simulation and scenario modelling in urban design
  • Human activity patterns and socio-spatial behaviour analysis
  • Translating data insights into design strategies
  • Designing adaptive, resilient, and responsive urban environments

Your Instructor

Mahmud Tantoush
Mahmud Tantoush

Senior Lecturer | Manchester School of Architecture

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Dr Mahmud Tantoush leads the [CPU]Ai atelier, where his teaching focuses on computational design, urban analytics, and the integration of AI into design processes. With several years of experience teaching complexity-based computational approaches to architectural and urban design, he embeds his published research and theoretical contributions on sustainable futures into both teaching and supervision. He also leads the Master of Architecture (Part 2) design studio modules (Studio 1, 2 and 3), where students critically explore the future of the profession and collaborate with nationally leading practices. His research as part of the ARO/[CPU]Lab focuses on how cities can be analysed and designed in more sustainable ways, combining complexity theories and modelling towards sustainable futures using new methodologies including AI Machine Leaning and Urban Big Data. Mahmud has been involved in funded research projects funded by Horizon Europe and UKRI, and he supervises PhD students working on urban analytics and sustainable future cities.

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We are a registered provider with 327+ associations and regulatory bodies worldwide. We operate across 29 global markets including Canada, the US, Australia, and the UK. Every course page clearly displays its specific accreditations. Upon completion, you receive a professional certificate that can be validated online. Our certificates include all necessary accreditation details, credit hours, and completion dates, and are formatted specifically to meet the submission requirements of most global regulatory bodies.