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DelftX: AI in Architectural Design

Learn about the elements of AI, machine learning and computer vision as applied to architectural design practice and research.

AI in Architectural Design
4 weeks
2–4 hours per week
Instructor-paced
Instructor-led on a course schedule
Free
Optional upgrade available

There is one session available:

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Starts Sep 24
Ends Nov 4
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AI in Architectural Design

About this course

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Are you navigating through the maze of AI discussions in everyday conversations? Do you feel overwhelmed and find it challenging to keep up with the constant flow of AI news? Or perhaps you are enthusiastic about AI and its transformative power in design practices. This course will shed light on the science behind the most popular AI tools.

Are you an architect concerned about the potential impact of AI on your role? If you're eager to upskill, this course is designed to help you manage expectations and enhance your skills, ensuring greater job competency in the evolving landscape of design, data and AI.

The course goes beyond introducing AI as merely a tool but presents a new methodology for scientific design thinking, focusing on a few key elements to empower your designs with Artificial Intelligence.

The content of the course is specifically suitable for architects in practice or architectural students searching for something outside of the architecture field, possibly gaining new skills in programming and AI to fit into more diverse job opportunities.

The learning journey starts with understanding machine learning as the science behind the AI technology. Further, the focus is established on computer vision as the “eye of AI” within the domain of architectural design. You will discover how the computer vision technology reshapes the landscape of design possibilities and merges creativity and technology.

You will also be introduced to algorithmic and data-driven thinking, data patterns, and the transformative power of learning systems. Hands-on experience with Python programming is included in the course. The assessments will include a brief machine learning project that combines theory with real-world application.

Both scientific and computational approaches are presented in the course. You will learn how to formulate hypotheses and explore innovative ways of testing and validating your design concepts. By exploring statistical machine learning for design validation, you will be able to translate your design hypotheses into reality by employing intuitive statistical machine learning methods, refining your designs through empirical validation and at the same time acquiring the skills to make informed design decisions.

At a glance

  • Institution: DelftX
  • Subject: Design
  • Level: Introductory
  • Prerequisites:
    None
  • Language: English
  • Video Transcript: English

What you'll learn

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  • Explain machine learning as a science behind AI technology.
  • Describe what computer vision is and how it is positioned with respect to AI technology.
  • Recognise some applications of computer vision in architectural design.
  • Learn how and where to find data related to the built environment.
  • Learn how to re-think design as a scientific quest.
  • Gain hands-on experience of Python programming and using relevant libraries to conduct a small machine learning project with real data.

Syllabus

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Module 1: Understanding AI

  • Data, information, knowledge
  • AI, machine learning and computer vision
  • Deep learning frameworks, Supervised learning, Clustering and Unsupervised learning, Reinforcement Learning, Dimensionality Reduction, Visualization

Module 2: Comprehension - Machine learning for design problems

  • Algorithmic thinking vs Data driven thinking.
  • Validating architectural quality with data

Module 3: Application - The design question

  • Apply AI knowledge to re-formulate a design question
  • Defining real-world problems with different approaches (algorithmic, data driven, machine learning)

Module 4: Analysis - Python programming for the design question

  • Learn how to use Python programming and relevant libraries to collect and curate data to approach the formulated design question.
  • Build up practical skills to approach the data-driven design questions.

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

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Price

$109 USD

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Expires on Oct 22

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