Materials Informatics Graduate Certificate Program (MI GCP)
The Materials Informatics (MI) Graduate Certificate Program (GCP) is designed for interdisciplinary graduate education at the intersection of materials science, engineering, and data science with the aim of preparing the next generation of materials engineers given the growing demand for data-science skills and knowledge of the artificial intelligence. The skills and knowledge obtained will serve as foundation for the understanding of materials informatics and high throughput materials discovery that will improve career prospects.
Why Study Materials Informatics?
As the use of data science tools matures and spreads to different industries and domains, the demand for professionals with domain knowledge and the ability to handle heterogeneous data is increasing.
Certificate Completion Requirements
A total of four classes (12 credit hours) is required, including the core course MSE 723 (3 credit hours) and three MSE and ST or MA elective courses (9 credit hours). By judicious selection of elective courses, in consultation with the MI GCP Coordinator, students can customize their GCP to focus on areas of interest to them.
* signifies courses that are offered online
MSE 723* Materials Informatics
The MSE 723 course aims to introduce the emergent field of materials informatics and current approaches that employ informatics and experimental and computational data to accelerate the process of materials optimization, discovery and development. An emphasis will be placed on practical implementation of machine-learning techniques to various materials science problems.
|MSE ELECTIVE COURSES||ST/MA ELECTIVE COURSES|
|Select at least one of the following:||Select at least one of the following:|
|MSE 710* Elements of Crystallography and Diffraction||ST 517* Statistical Methods I (or equivalent introductory to statistics course). ST grad students are not permitted to use it for certificate credit|
|MSE 721* Nanoscale Simulations and Modeling||ST 540 Applied Bayesian Analysis|
|MSE 724* Quantitative Materials Characterization Techniques||ST 533 Applied Spatial Statistics|
|MA 540* Uncertainty Quantification for Physical and Biological Models|
The fourth course will be taken from outside of the student’s degree department. For example, an MSE student’s fourth course must be from the ST or MA list (above), whereas a ST or MA student’s fourth course must be from the MSE list (above).
|How to Apply||
|Academic Performance Requirements||
MI GCP Coordinator
Yaroslava G. Yingling, Professor of Materials Science and Engineering