Lead Instructor(s)
Date(s)
Jul 21 - 25, 2025
Registration Deadline
Course Fee
$4,700
CEUs
3.3 CEUs

Increase the efficiency of your engineering workflow with strategies fueled by the latest advancements in AI. In this highly practical course, you’ll learn how to use AI and machine learning tools to amplify classical methods in engineering—fueling your organization’s ability to produce high volumes of complex, customized products.

This course may be taken individually or as part of the Professional Certificate Program in Design & Manufacturing or the Professional Certificate Program in Machine Learning & Artificial Intelligence.

COURSE OVERVIEW

“This course will show you how to integrate cutting-edge AI techniques into your workflows, enabling you to generate more design variants, predict performance, and bridge the gap between simulation and reality, all while significantly improving speed and efficiency.” – Professor Wojciech Matusik 

AI is redefining the way engineering work gets done. Tasks that may have once taken days can now be completed in just hours—if you adapt your workflow with the right tools. 

In this highly interactive course, you will learn to develop a highly efficient end-to-end design and manufacturing workflow powered by AI and machine learning. Over five days, you will gain hands-on experience with the methods that are advancing digital manufacturing across the entire design ecosystem, including the use of large language models.

Through dynamic lectures, group discussions, and generative design sessions, you will master AI-driven techniques for: 

  • Optimizing and controlling manufacturing workflow processes
  • Supercharging design automation and customization
  • Translating functional specifications of objects to manufacturable designs

This is a must-take course for any engineer or engineering manager working in product design and manufacturing. You will leave the experience with a practical set of skills that you can immediately use to enhance the efficiency, accuracy, and speed of your daily work.   

LEARNING OUTCOMES
  • Develop an intelligent design and manufacturing workflow built on cutting-edge AI and machine learning.
  • Recognize the applications and limitations of advanced manufacturing tools.
  • Use AI tools to optimize manufacturing processes and workflows.
  • Apply traditional and AI-based geometric representations for digital manufacturing.
  • Automate mass-customization of designs.
  • Predict design performance with virtual testing, numerical simulation, and other computational methods.
  • Build performance-driven design workflows.
  • Implement principles of generative and inverse design.
  • Use generative design methods to design and optimize objects for multiple objectives and across multiple domains.
  • Design and build machine learning models that enable customization.
  • Master numerical optimization techniques for machine learning.
WHO SHOULD ATTEND

This course is designed for professionals from a range of industries, including healthcare, electronics, transportation, architecture, aerospace, and defense. 

Specifically, this course is ideal for:

  • Engineers and engineering managers who want to increase the speed at which they can translate concepts into physical objects and products.
  • Designers, product managers, and production managers who want to improve their design and manufacturing processes. 
  • Scientists, educators and research and development managers looking to incorporate the latest AI-driven strategies into their workflows.  

Requirements
Laptops or tablets with Windows and with which you have administrator privileges are required for this course.

FACULTY BIO

Wojciech Matusik
Professor Wojciech Matusik is an Associate Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT, where he leads the Computational Fabrication Group. Professor Matusik is a cofounder and CTO at Inkbit. Before coming to MIT, he worked at Mitsubishi Electric Research Laboratories, Adobe Systems, and Disney Research Zurich in computer graphics and additive manufacturing research. His research interests are in direct digital manufacturing and computer graphics. Professor Matusik holds more than 40 U.S. patents. In 2004, he was named one of the World's Top 100 Young Innovators by MIT Technology Review Magazine. In 2012, Professor Matusik received the DARPA Young Faculty Award and was named a Sloan Research Fellow. He currently serves on the DARPA ISAT Study Group.