Training Overview

Training Classroom

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)
  2. Fundamentals of Materials Science for Data Scientists (FALL ME 555 Materials Synthesis and Processing, David Mitzi)
  3. Applications in Data and Materials Science (SPRING ME 555/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

Thoughout 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.


aiM certificate



Training Schedule for aiM Certificate




Year 1

Year 2 

Years 3-5 


 Boot Camp

Core Courses

Year-Long Core Course 

Experiential Training 


  • Overview

  • Materials+Data Science, and Statistics Fundamentals

  • Team Building

  • Professional Skills Development

  • Fundamentals of Data Science for Material Scientists and/or 

  • 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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