60.009 Data and Design

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* Course is conducted online by Zhejiang University

Course Description

Data science and artificial intelligence are becoming the new engine for design related activities. Decisions are made from sophisticated data analysis. Designers understand better about customers through data mining and visualization. Designers also need artificial intelligence technologies to speed-up their work efficiency as well as co-create designs. This course will strengthen the connection between computer science with design and introduce approaches for applying AI techniques in the context of design.

Prerequisites

Students should have the basic knowledge about Python programming, data science and machine learning.

Mutually Exclusive Subject:
50.038 Computational Data Science

Learning Objectives

The course aims to instruct the methods of applying data science and artificial intelligence in the context of design, including data-driven methods, semantic networks for design creativity, AI techniques related to design and their applications. Overall, this course covers three aspects:

  1. Data-driven design: the concept and significance of data science for design, understanding of data-driven methods, semantic networks for design creativity and data-driven design.
  2. Design intelligence: understanding of generative models, style transfer, image generation and intelligent UI in the context of design.
  3. Practice of applying data science and AI in design: learning to apply data-driven methods and AI design methods to design tasks in workshops, tutorials, and the course project.

Measurable Outcomes

  1. Carry out applications of data-driven design, including design creativity
  2. Apply generative models, style transfer, image generation and intelligent UI in the context of design
  3. Apply the design process and tools for design intelligence

Textbook(s) and/or Other Required Material

  • Armstrong, H. (2021). Big Data, Big Design: Why Designers Should Care about Artificial Intelligence. Chronicle Books.
  • Liu, A., Wang, Y., & Wang, X. (2022). Data-Driven Engineering Design. In Data-Driven Engineering Design (pp. 1-22). Springer, Cham.
  • Kleppmann, M. (2017). Designing data-intensive applications: The big ideas behind reliable, scalable, and maintainable systems. O’Reilly Media, Inc..
  • Pham, D. T. (Ed.). (2012). Artificial intelligence in design. Springer Science & Business Media.
  • Tong, C., & Sriram, D. (Eds.). (2012). Artificial Intelligence in Engineering Design: Volume III: Knowledge Acquisition, Commercial Systems, And Integrated Environments. Elsevier.

Image Credit Unsplash

2023-10-09T18:02:17+08:00