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Lead Instructor(s)
Jul 15 - 18, 2024
Registration Deadline
On Campus
Course Length
4 days
Course Fee
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Manufacturing. Medicine. Robotics. Agriculture. The latest imaging and machine learning breakthroughs are opening up enormous opportunities across myriad industries. Do you have the advanced knowledge to keep pace? Take a deep dive into the latest imaging technologies and trends, spanning optical, ultrasound, acoustic, and RADAR systems—and master applied machine learning strategies for image formation and analysis.

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

Course Overview

In this intensive four-day program, taught by renowned MIT product development expert Dr. Brian Anthony, you’ll explore the sensors, analytics, and decision-making of optical, ultrasound, acoustic, and RADAR imaging technologies and learn more about their commercial possibilities—both today and in the future. 
Alongside accomplished global peers, you’ll survey the landscape of imaging hardware, sensors, and computational techniques and algorithms. Course learning will happen through a combination of case study exploration, hands-on exercises with imaging devices, open-ended exercises (rapid prototyping), and participatory discussions. You’ll also tour the MIT.nano Immersion Lab, the Center for Clinical and Translation Research, the FrED Factory, and learn more about breakthrough research and innovation projects at MIT. 
You’ll emerge from the experience with the advanced tools and strategies you need to design and use imaging systems, complete with hardware and software, within your own products. This essential skill set will help you maintain a competitive advantage in this rapidly evolving technology area.

Certificate of Completion from MIT Professional Education

Imaging and Machine Learning in Manufacturing cert image
Learning Outcomes
  • Design and assemble imaging systems and imaging sensors, with attention to hardware and software interaction
  • Specify and select commercially available solutions and components
  • Explore a range of imaging building block technologies, including sensors, hardware systems, analytics, and machine learning
  • Learn how to aggregate and analyze many types of image data
  • Use algorithms to turn image data into effective automated predictions 
  • Implement, apply, and test basic image-based machine-learning methods
Who Should Attend

This course is designed for participants who have a bachelor's degree (at a minimum) and at least three years of professional experience. Professionals who will particularly benefit from the curriculum include:

  • Developers of imaging systems or components
  • Users of imaging technology
  • Purchasers of imaging technology, such as automotive and government professionals
  • Professionals seeking to use or add imaging technology to their product or develop an imaging-based product
  • Industry or government personnel who want to learn how imaging systems work
  • Industry or government supervisors seeking to quickly educate employees

Computer Requirements

A laptop for which you have administrator privileges is required. Computing activities will include image construction and analysis in Python and Matlab.


This course runs 9:00am-5:00pm each day.


Tools of the day:
Imaging sensors - space
Imaging algorithms
Learning in acquisition

Mode: Ultrasound
Cases of the Day
Diagnostic Imaging
In-line inspection

Medical and Manufacturing - decision making


Tools of the day:
Image simulation
Synthetic Training
Learning in Formation

Mode: Acoustics and Light
Cases of the Day
Automotive and autonomous systems
Ambient health monitoring

Real-time decision making


Tools of the day:
Inverse Problems

Cases of the Day
Classic RADAR
RADAR at home

Prediction and Design


Tools of the day:
Imaging sensors - time and space
Unsupervised learning

Multi-modal + Camera
Cases of the Day

Complex Assembly and Test


Download the Course Brochure
Imaging & Machine Learning in Manufacturing, Medicine, and More: The New & Next