This course aims to provide a succinct overview of the emerging discipline of Materials Informatics at the intersection of materials science, computational science, and information science. Attention is drawn to specific opportunities afforded by this new field in accelerating materials development and deployment efforts. A particular emphasis is placed on materials exhibiting hierarchical internal structures spanning multiple length/structure scales and the impediments involved in establishing invertible process-structure-property (PSP) linkages for these materials. More specifically, it is argued that modern data sciences (including advanced statistics, dimensionality reduction, and formulation of metamodels) and innovative cyberinfrastructure tools (including integration platforms, databases, and customized tools for enhancement of collaborations among cross-disciplinary team members) are likely to play a critical and pivotal role in addressing the above challenges.

Materials Data Sciences and Informatics

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5 assignments
Taught in English
There are 6 modules in this course
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SG
5.0
Reviewed on Sep 7, 2020
I take this opportunity to express sincere gratitude to Dr Surya Kalidindi. Thank you COURSERA yet again.
MR
5.0
Reviewed on Jul 11, 2024
This course effectively bridged the gap between materials science and data-driven methodologies, introducing advanced techniques for managing and analyzing complex materials data.
RR
5.0
Reviewed on Sep 22, 2018
Machine learning part and its application to material science was interesting but informative contents like material dev eco system and whole week 1 was more informative than logical
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