Associate Professor Taubman College of Architecture and Urban Planning
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Creative Coding for Designers Using Python,marks the final installment in the comprehensive three-course specialization, aimed at significantly enhancing the programming capabilities of designers, artists, and visual thinkers through Python. As the advanced course in the series, Creative Coding for Designers Using Python adopts a project-based learning strategy to consolidate and apply the skills acquired from the first two courses. In this course, you’ll focus on dynamic simulations and procedural content generation, offering a deeper dive into Python's application in visual design and digital art. Designed for individuals who have grasped the basics of Python, including its syntax, data structures, and object-oriented programming principles, this course delves into sophisticated topics. Leveraging the Processing platform with Python, you’ll engage in interactive projects that transform theoretical knowledge into tangible outputs, bridging the gap between technical proficiency and artistic creativity.
Creative Coding for Designers Using Python is structured as an educational journey that combines technology and art, equipping participants with the skills to explore advanced digital design techniques. This course offers the tools and conceptual understanding necessary for the innovative application of Python in creating digital art and design projects.
This is the third and final course in a three-part series, Programming for Designers, aimed at equipping designers with essential computational design skills.
Welcome to Creative Coding for Designers Using Python, an advanced course in the Programming for Designers series. Dive into particle systems, vector fields, and ecosystem simulations to explore complex patterns and interactions. Learn advanced algorithms like A-Star and wave function collapse for generative design in architecture, gaming, and digital art. This course will expand your creative coding skills and empower you to design visually captivating and algorithmically rich projects.
This abbreviated syllabus description was created with the help of AI tools and reviewed by staff. The full syllabus is available to those who enroll in the course.
Module 1: Particle Systems
Module 2: Vector Fields
Module 3: Ecosystem Simulation
Module 4: Pathfinding
Module 5: Wave Function Collapse
To pass the course and earn the certificate, you must achieve an overall grade of 80%. Grades are based entirely on module review quizzes, with each quiz accounting for 20% of your final grade.
Associate Professor Taubman College of Architecture and Urban Planning
Course content developed by U-M faculty and managed by the university. Faculty titles and affiliations are updated periodically.
Advanced Level
Participants are advised to have some familiarity with design environments, including CAAD software, graphic design software, or 3D model software.