Training Overview

aiM Symposium

Each aiM Trainee will engage in coursework integrated with parallel professional skills development and an experiential internship with opportunities to apply their knowledge and skills.

Boot Camp

An orientation boot camp will provide fundamental knowledge in AI + Materials Science and development of professional skills (communication, collaboration, and teamwork skills).

Core Courses

  1. Fundamentals of Data Science for Materials Scientists (FALL CS 671D/ECE 687D/STA 671D Theory and Algorithms for Machine Learning, Cynthia Rudin; ME 555-09/CEE 690 Data Science and Machine Learning for Applied Science and Engineering, David Carlson/Jonathan Holt)
  2. Fundamentals of Materials Science for Data Scientists (FALL ME 562 Materials Synthesis and Processing, David Mitzi)
  3. Applications in Data and Materials Science (SPRING ME 582/CS 590)
  4. Joint AI in Materials Capstone Project Course (Fall 1 credit + Spring 2 credits)

Experiential Internships 

After two years of training in fundamentals and skills application, aiM Trainees will be prepared for an Summer (or extented) external internship with an industry partner or national laboratory. These collaborative internships will afford access to world-class expertise, unique experiments, and facilities to complement the skills aiM Trainees learn through coursework and research to apply their skills to real-world problems in data-driven materials science and build their professional networks.

An ongoing professional development program

Throughout the program experience students will develop professionally guided by an Individual Development Plan (IDP) including “professional skills” and “technical skills”. Professional skills training will include formal and informal communication as well as K-12 outreach, mentor and mentee training, leadership and collaboration skills, and other skills critical for workforce success.

Training Schedule for aiM Certificate

aiM Certification


Year 1

Year 2

Years 3-5

Boot Camp

Core Courses

Year-Long Core Course 

Experiential Training 


Materials+Data Science, and Statistics Fundamentals

Team Building

Professional Skills Development

Fundamentals of Data Science for Material Scientists


Fundamentals of Materials Science for Data Scientists

Applications in Data and Materials Science

Joint AI in Materials Capstone Project Course

Industry or National Lab Internship

Teaching or Mentoring Experiences


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