Overview
What you will study
Over the next few decades, industries around the world will transition to a new economy in which highly complex, customizable products will be manufactured on-demand using intelligent manufacturing systems. In a number of fields, this change is already underway—for example, additive manufacturing is revolutionizing the production of consumer, aerospace, automotive, and medical parts. To stay ahead, professionals need a thorough understanding of the AI-powered strategies and tools that are enabling these rapid advancements—and a plan for implementing them in their own organizations.
The AI for Computational Design and Manufacturing course offered by Massachusetts Institute of Technology (MIT) provides an introduction to developing end-to-end AI-based design and manufacturing workflows. Over the course of five days, you will explore how AI methods are advancing digital manufacturing and the entire design ecosystem. In this course, you will also:
- Learn how AI methods can be used in a manufacturing workflow for process optimization and control
- Discover AI/machine learning methods that enable design automation and customization
- Explore AI/machine learning methods for performance-driven design that automatically translate functional specifications of objects to manufacturable designs
Programme Structure
The program focuses on:
- Learn how to develop an intelligent design and manufacturing workflow using the latest AI/machine learning methods.
- Recognize the capabilities and limitations of current advanced manufacturing hardware.
- Enhance your ability to use AI tools for optimizing manufacturing processes.
- Increase your understanding of traditional and AI-based geometric representations.
- Explore how to automatically mass-customize designs.
- Learn how to predict design performance using virtual testing, numerical simulation, and AI methods.
- Delve into performance-driven design workflow, as well as principles of generative and inverse design.
- Design objects using generative design methods.
- Acquire experience designing and optimizing objects for multiple objectives and across multiple domains.
- Design and build data-driven (machine learning) models that drive design customization.
- Master principles of numerical optimization techniques for machine learning.
Key information
Duration
- Full-time
- 5 days
- Part-time
- 5 days
Start dates & application deadlines
- Starting
- Apply before
-
Language
Credits
Delivered
Disciplines
Artificial Intelligence Production and Manufacturing Engineering View 25 other Short Courses in Production and Manufacturing Engineering in United StatesWhat students do after studying Computer Science & IT
This information is based on LinkedIn alumni data for graduates from 2018 to 2024 and may not fully represent all career outcomes
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Student insurance
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:
- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
We partnered with Aon to provide you with the best affordable student insurance, for a carefree experience away from home.
Get your student insurance nowStarting from €0.53/day, free cancellation any time.
Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at Massachusetts Institute of Technology (MIT) and/or in United States, please visit Student Insurance Portal.
Other requirements
General requirements
- This course is designed for engineers, designers, product managers, production managers, research and development managers, scientists and educators in industries that are involved in translating concepts to physical objects/products. Relevant areas include consumer products, medical devices, textile, packaging, electronics, automotive, chemical, architecture, aerospace, and defense.
Technological requirements
- Laptops or tablets with Windows and with which you have administrator privileges are required for this course.
Tuition Fee
-
International
4700 USD/fullTuition FeeBased on the tuition of 4700 USD for the full programme during 5 days. -
National
4700 USD/fullTuition FeeBased on the tuition of 4700 USD for the full programme during 5 days.
Living costs for Boston
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.