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Materials Computation and Data Science

This concentration area is appropriate for those planning a career in computational materials science and engineering and/or in materials data science. In computational materials science you will learn about the modeling and simulation of material structure and dynamics relevant to real materials problems, often occurring across multiple time and length scales. Materials data science will provide you with knowledge of computational tools that utilize large amounts of information data for use in decisions related to materials selection and design.

Recommended math elective

Choose one course from the list on B.S. Degree Requirements. If you don't have a preference, selecting INDE 315 (Probability and Statistics for Engineers) is encouraged (NOTE: INDE 315 can count EITHER towards the Math Elective OR as one of the Engineering Fundamentals Electives, but it cannot count in both categories).

Recommended natural science electives

Choose two.

Course and Credits Title Notes
 

CHEM 162/165 (5)

General Chemistry - 3rd quarter Prereq 1.7 in CHEM 152; this course is prereq for CHEM 237
PHYS 224 (3) Thermal Physics  Prereq MATH 126/136 and PHYS 123
PHYS 225 (4) Introduction to Quantum Mechanics Prereq. 2.0 in  PHYS 227; or a 2.0 in  PHYS 123 and MATH 136; or a 2.0 in PHYS 123, MATH 207 (or MATH 307), and MATH 208 (or MATH 308).
PHYS 227 (4) Elementary Mathematical Physics Prereq 2.0 in PHYS 121, 122, 123, and MATH 126

PHYS 228 (4)

Elementary Mathematical  Physics Prereq 2.0 in PHYS 227

Recommended engineering fundamentals electives

Choose 8 credits.

Course and Credits Title Notes
CSE 143 (4) Computer Programming II Prereq is CSE 142
CSE 160 (4) Data Programming Introductory Data Programming course for students who took AMATH 301
CSE 164 (4) Intermediate Data Programming Prereq is CSE 142, CSE 143, or CSE 160
CSE 180 (4) Introduction to Data Science  
IND E 250 (4) Fundamentals of Engineering Economy  

Recommended technical elective requirements

A minimum of 9 credits of MSE classes.

Course and Credits Title Notes
MSE 477 (3) Data Science and Materials Informatics  
MSE 478 (3) Materials and Device Modeling

Prereq is MSE 477

MSE 479 (3) Big Data for Materials Science Prereq is MSE 477
AMATH 401 (3) Vector Calculus and Complex Variables Prereq is Math 126/136
AMATH 403 (3) Methods for Partial Differential Equations Prereqs AMATH 401; either AMATH 351, MATH 136, or MATH 207 (or MATH 307)
CSE 373 (4) Data Structures and Algorithms Prereq is CSE 143
CSE 412 (4) Introduction to Data Visualization Prereq is CSE 143 or CSE 163
CSE 414 (4) Database Systems Prereq is CSE 143
BIOEN 504 (4) Introduction to Technology Commercialization  
ENGR 321 Engineering Internship Education Earn 1 credit for an internship 1-20 hours/week, and 2 credits for an internship 20 hours/week+. Can count up to 4 credits of internship towards your degree

Impact areas