Training at the Nexis of AI and Materials

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Photo of Joint NRT Symposium attendees in Chicago.

Recommended Core Courses

1.  CEE 580/ME555 Data Science and Machine Learning for Applied Science and Engineering, David Carlson/Jonathan Holt)
   and/or 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 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 ME555)

Experiential Internships 

Students are well-prepared and encouraged to pursue 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 students learn through coursework and research to apply their skills to real-world problems in data-driven materials science and build their professional networks. Reach out to the AI + Materials Certificate Coordinator, Pratt GSPS or your DGS/DMS for leads.