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Lead Instructor(s)
Date(s)
Jul 27 - 29, 2020
Registration Deadline
Location
On Campus
Course Length
3 Days
Course Fee
$3,300
CEUs
1.9
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Description

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

Advancements in material design are shaping the future of AI. New material properties and structures are helping organizations overcome traditional constraints—transforming the way energy and data operating hardware is developed. In turn, these changes are powering unprecedented commercial opportunities in manufacturing, ranging from electric vehicles to mobile device batteries.

To help you capitalize on these exciting developments, MIT Professional Education is proud to introduce Device Manufacturing: From Energy to AI. In this three-day course, you will explore fundamental manufacturing and design considerations for solid state devices, including energy storage and information transmitting devices for AI. You will also acquire cutting-edge manufacturing and performance strategies that can be implemented across a variety of applications—from solid state batteries used in electric vehicles to sensor and neuromorphic computing hardware for AI.

Register today to begin powering your AI applications with the latest manufacturing and design frameworks.

Participant Takeaways

  • Explore tech trends and manufacturing strategies for AI energy and information devices
  • Master the fundamentals for manufacturing solid state materials
  • Acquire strategies for device and performance engineering, including manufacturing innovations ranging from large scale and powder manufacturing to thin film manufacturing
  • Learn how to determine the ideal processing route for device architecture and functional property design
  • Examine real-world applications of energy and AI devices across a range of industries

Who Should Attend

This course is designed for professionals who are active in—or wish to learn more about—material manufacturing and synthesis targeting solid state components, in industries such as energy, automotive, electronics, consumer products, medical devices, material processes, and AI engineering. Ideal roles include:

  • Manufacturing engineers
  • Product designers
  • Research engineers
  • Material engineers
  • VPs of product development and manufacturing
  • Technology and innovation strategists

Program Outline

Class is held 9:30 am - 5:30 pm each day of the course. There is a networking reception at 6:00 pm on Monday.

Day One

  • 9:30-10:30 am - Introduction to Society’s Needs and Recent Developments of AI and Energy Devices (Instructor: Jennifer Rupp)
  • 10:30-11:00 am - Coffee Break  
  • 11:00-12:30 pm - Energy and AI Information Landscape: Emerging Trends (Instructor: Jennifer Rupp)
  • 12:30-1:30 pm - Lunch  
  • 1:30-3:00 pm - Manufacturing materials and device interfaces over length scales: Powder, large-scale component, thin film design for circuitry (Instructor: Jennifer Rupp)
  • 3:00-3:30 pm - Coffee Break  
  • 3:30-5:30 pm - Lab 1: Ceramic Processing (Instructor: TBA)
  • 6:00-8:00 pm - Special Evening: Social & Networking Reception

   Day Two

  • 9:30-10:30 am - Review of work done in previous day’s Lab 1 (Instructor: Jennifer Rupp)
  • 10:30-11:00 am - Coffee Break
  • 11:00-12:30 pm - Device Design and Performance Engineering Industry Focus "Energy I": Batteries (Instructor: Jennifer Rupp)
  • 12:30-1:30 pm - Lunch  
  • 1:30-3:00 pm - Device Design and Performance Engineering Industry Focus "Energy II": Fuel Cells (Instructor: Jennifer Rupp)
  • 3:00-3:30 pm - Coffee Break  
  • 3:30-5:30 pm - Lab 2: Energy Devices (Instructor: Jennifer Rupp)

Day Three

  • 9:30-10:30 am - Review of work done in previous day’s Lab 2 (Instructor: Jennifer Rupp)
  • 10:30-11:00 am - Coffee Break  
  • 11:00-12:30 pm - Device Design and Performance Engineering Industry Focus "Energy III": Renewable Fuel Conversion (Instructor: Jennifer Rupp)
  • 12:30-1:30 pm - Working Lunch: Networking and Discussion on Industry Applications and Needs (Instructor: Jennifer Rupp)
  • 1:30-3:00 pm - Device Design and Performance Engineering Industry Focus "AI & Information II": Memories and Neuromorphic Computing and Sensing for Artificial Intelligence (Instructor: Jennifer Rupp)
  • 3:00-3:30 pm - Coffee Break
  • 3:30-5:30 pm - Lab 3: Neuromorphic computing and memories for AI (Instructor: TBA) 
Content

The type of content you will learn in this course, whether it's a foundational understanding of the subject, the hottest trends and developments in the field, or suggested practical applications for industry.

Fundamentals: Core concepts, understandings, and tools - 40%|Latest Developments: Recent advances and future trends - 30%|Industry Applications: Linking theory and real-world - 30%
40|30|30
Delivery Methods

How the course is taught, from traditional classroom lectures and riveting discussions to group projects to engaging and interactive simulations and exercises with your peers.

Lecture: Delivery of material in a lecture format - 50%|Discussion or Groupwork: Participatory learning - 25%|Labs: Demonstrations, experiments, simulations - 25%
50|25|25
Levels

What level of expertise and familiarity the material in this course assumes you have. The greater the amount of introductory material taught in the course, the less you will need to be familiar with when you attend.

Introductory: Appropriate for a general audience - 35%|Specialized: Assumes experience in practice area or field - 50%|Advanced: In-depth explorations at the graduate level - 15%
35|50|15