Computational Design Grasshopper 3D Rhinoceros Industrial Designer

Computational Design LIVE Workshop*

Join our LIVE Computational Design (CoDe) Workshop to explore data-driven design, lattice structure, topology optimization, generative design, machine learning classification, and various computational design workflows.

*Rhino for Windows Only. For Mac Users, use Boot Camp or Parallels to run Rhino for Windows.

Additional Information:

  • Are you finding it challenging to integrate Computational Design into your projects, unsure about which data-driven strategies to implement, or how to effectively apply topology optimization and generative design? Navigating the complexities of Computational Design can be daunting, especially without a solid understanding of its core principles, like lattice structures, machine learning classification, and other computational workflows.

    Join our LIVE Computational Design Workshop to master these cutting-edge techniques, with a special focus on the use of Grasshopper 3D and Rhino. In this comprehensive course, we'll dive deep into the essentials of data-driven design, exploring the intricacies of lattice structures and topology optimization. You'll learn how Grasshopper 3D and Rhino can be powerful tools in leveraging generative design and machine learning to create innovative, efficient designs.

    Our course will also cover practical applications in 3D printing, showing you how to bring your computational designs to life. This hands-on training will guide you through various computational workflows, enhancing your design projects with 3D printed models and prototypes. Whether you're aiming to optimize your designs, integrate advanced computational strategies with Grasshopper 3D and Rhino, or explore the exciting possibilities of 3D printing, this workshop is your gateway to mastering Computational Design

  • WINDOWS USERS ONLY

    Day 1

    • Intro Computational Design
    • Theory Building Fundamentals
    • Exploring Generative Design
    • Understanding Search Space
    • Generative Wheel Design
    • Voxel Workflow Exploration
    • CT Scan to 3D Modeling
    • Prosthetic Design Overlay
    • Foundation of Lattice Structures

    Day 2

    • Advanced Lattice Structures
    • Lattice for Shoe Midsoles
    • Topology Optimization
    • Optimized Table Linkage
    • Machine Learning
    • Panel Rationalization
    • Data-Driven Design
    • Crash Data Helmet Design

    Assets:
    https://grabcad.com/library/adidas-tubular-nova-pk-1

  • • Live class recording
    • Reading materials & References
    • 3D files and Resources
    • Access to “Rhinoceros” Group

  • • Online LIVE Zoom
    • 12 Hours
    • English

Topological Optimization Grasshopper 3D Rhino Computational Design for Ideation Industrial Design Cademy
Machine Learning Paneling Lunchbox Grasshopper Rhinoceros 3D Computational Design for Ideation Industrial Design Cademy xyz
Lattice Cube Grasshopper 3D Rhinoceros Industrial design Cademy xyz Creativemutation
Crash Helmet Data Driven Design Lunchbox Grasshopper 3D Rhinoceros Industrial design Cademy xyz Creativemutation
Prosthetic CT Scan Grasshopper 3D Rhinoceros Industrial design Cademy xyz Creativemutation
Voxel Lattice Computational Design for Ideation Industrial Design Cademy xyz
Lattice Structure Shoes 3D printed Computational Design for Ideation Industrial Designer
Prosthetic CT Scan Grasshopper 3D Rhinoceros Industrial design Cademy xyz Creativemutation
Generative Design Wheel Rim Grasshopper 3D Rhinoceros Industrial design Cademy xyz Creativemutation

About Instructor :

Aman is an industrial designer known for his expertise in 3D surface models and textures. He's consulted for companies like Design Partners, Logitech, BSH, and Hamilton Beach. Aman shares his knowledge through live classes with design students and professionals globally.

Aman Rai Agrawal | CreativeMutation
Industrial & Computational Designer

Would you like to join our Computational Design Grasshopper LIVE Workshop? Register for the Upcoming LIVE class.

Check our past classes here.