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AI-Driven Computational Design
Elevate and optimize design and production processes for your organization through state-of-the-art AI methods for design, engineering, and advanced manufacturing.
START DATE
December 3, 2024
DURATION
6 weeks
COMMITMENT
6-8 hours per week
PRICE
US$1,800
LANGUAGE
English
FORMAT
Online
Course modules will pause on December 23, 2024, and resume on January 7, 2025.
AI-Driven Computational Design
This course delves into cutting-edge AI and machine-learning methods to develop AI-based designs of objects and physical experiments, produce manufacturing workflows, and convert digital designs into manufacturing instructions.
- Understand how to develop an intelligent design and manufacturing workflow by integrating cutting-edge AI and machine learning techniques.
- Reduce manufacturing lead time through AI-driven industrial processes.
- Increase workforce productivity by introducing advanced digital design and manufacturing techniques.
- Reduce R&D costs by introducing AI/machine learning methods to convert performance-driven designs into manufacturable designs.
- Secure a competitive edge by enhancing technological efficiency, design accuracy, and manufacturing speed.
- Create three-dimensional objects employing generative design techniques.
THROUGHOUT THIS COURSE, YOU WILL:
CERTIFICATE
MEET YOUR INSTRUCTOR
WOJCIECH MATUSIK
Professor at the Department of Electrical Engineering and Computer Science
THE MIT XPRO LEARNING EXPERIENCE
WHAT IS THE COURSE COMPRISED OF?
This course follows intricately crafted modules that address developing intelligent design and manufacturing workflows.
- Module 1 – Introduction to Computational Design
- Design Representation
- Module 2 – Design Spaces
- Parametric Parametric Modeling
- Design Grammars
- Geometric Deformation Methods
- Module 3 – Generative AI for Learning Design Spaces
- Overview of Generative Methods
- Linear Models
- Non-linear Dimensionality Reduction
- GANs
- Diffusion Models
- Large Language Models
- Module 4 – Mapping Design to Performance Metrics
- Design vs. Performance
- Building AI Surrogate Models
- Performance Evaluation using Large Language Models
- Module 5 – Design Optimization (Inverse Design)
- Introduction to Inverse Design
- Examples of Inverse Design
- Design Optimization using Large Language Models
- AI Methods for Design Optimization with Limited Number of Experiments
- Module 6 – Generative AI for Creative Design
- Generative models for images and video
- Subjective Performance Evaluation
- User Experience Design Examples
- Future Directions for Generative AI in Creative Design
- Module 7 – Generative AI for Digital Manufacturing
- Translating Designs to Manufacturing Instructions
- Process Optimization
- Bridging the Gap between Digital Design and Reality