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Data Modeling and Programming for Architects

What Will Learn?

  • Course Aims
  • Course Goals
  • Decent Work and Economic Growth
  • Climate Action

Requirements

Description

  • English Description

    Integration of data modeling techniques into architectural design, focus on practical data challenges and identification, application, and comprehension of statistical methodologies for the built environment, architectural applications that employ algorithmic reasoning and practical algorithm implementation to improve problem-solving ability, introduction to programming foundations and Highlight of self-written scripts within architectural workflows, overview of architecture scripting languages such as Python, Processing, etc
  • Arabic Description

    Integration of data modeling techniques into architectural design, focus on practical data challenges and identification, application, and comprehension of statistical methodologies for the built environment, architectural applications that employ algorithmic reasoning and practical algorithm implementation to improve problem-solving ability, introduction to programming foundations and Highlight of self-written scripts within architectural workflows, overview of architecture scripting languages such as Python, Processing, etc
  • Department
    Architecture Engineering
  • Credit Hours
    2
  • Grades
    Total ( 100 ) = Midterm (10) + tr.Student Activities (55 = tr.Industry 0% , tr.Project 30% , tr.Self_learning 15% , tr.Seminar 10% ) + Exam Grade (35)
  • Hours
    Lecture Hours: 1, Tutorial Hours: 2, Lab Hours: 0
  • Required SWL
    75
  • Equivalent ECTS
    3
  • - Algorithmic Architecture, by Kostas Terzidis, Routledge, 2016 - Algorithmic Architecture, by Kostas Terzidis, Routledge, 2016 .