Trainee Certification Completion Course Options

Graduate curricula in data science and materials have historically been completely separate. The DIGI-MAT program is a fresh opportunity to integrate these curricula and create a focus on the convergent area of materials and data science. The DIGI-MAT program will create a new materials and data curriculum, centered on two entirely new semester-long courses, and a series of half-semester mini-courses available to students on an elective basis. A DIGI-MAT PhD student trainee will enter the curriculum through a new introductory course, then explore options from among existing elective courses and new DIGI-MAT mini-courses, and finally complete the curriculum in a new capstone design course.

All trainees are advised to partner with their advisor on course selection to assure selection aligns effectively with their research focus and future goals.

  • Cohort Zero (2018) — Will work closely with faculty advisor to review completed courses before selecting from any of the courses listed.
  • Cohort One (2019) — Will complete DIGItal MATerials courses first, then review elective course selection and discuss elective choices with faculty advisor before making a final decision.
  • Cohort Two (2020) — Will complete DIGItal MATerials courses first, then review elective course selection and discuss elective choices with faculty advisor before making a final decision.

Required Courses

Eight credit hours are required.

  • MSE/CSE 4XX DIGItal MATerials course (4 hours)
  • CSE 4XX Capstone project course (4 hours)

Elective Courses

Minimum 10 hours. Courses must include at least one selection from EACH category:

Category A: Data, Computer Science, Statistics

  • CS 412: Introduction to Data Mining (credit: 3 or 4 hours)
  • CS 446: Machine Learning (credit: 3 or 4 hours)
  • CS 511: Advanced Data Management (credit: 4 hours)
  • STAT 448: Advanced Data Analysis (credit: 4 hours)
  • STAT 542: Statistical Learning (credit: 4 hours)
  • STAT 545: Spatial Statistics (credit: 4 hours)
  • STAT 525: Computational Statistics (credit: 4 hours)
  • STAT 571: Multivariate Analysis (credit: 4 hours)
  • STAT/CS/CSE 4XX half-semester courses, TBA (credit: 2 hours)

Category B: Materials, Physics, Mechanics

  • PHYS 565: (same as ECE 535)
  • PHYS 486: Quantum Physics I (upper level undergrad)
  • PHYS 427: Thermal and Statistical Physics
  • PHYS 460: Condensed Matter
  • MSE 443: Design of Engineering Alloys (credit: 3 hours)
  • MSE 481: Intro to Transmission Electron Microscopy (3 or 4 hours)
  • MSE 485: Atomic Scale Simulations (credit: 3 or 4 hours)
  • MSE 487: Materials for Nanotechnology (3 or 4 hours)
  • CSE 450: Computational Mechanics (credit: 3 or 4 hours; same as TAM 470 — see TAM 470)
  • TAM 451: Intermediate Solid Mechanics (credit: 4 hours)
  • TAM 551: Solid Mechanics I (credit: 4 hours)
  • TAM 552: Solid Mechanics II (credit: 4 hours)
  • TAM 559: Atomistic Solid Mechanics (credit: 4 hours)
  • MSE/PHYS/TAM/CSE 4XX half-semester courses, TBA (credit: 2 hours)