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.
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Syllabus
Syllabus - What you will learn from this course
Week 1
Welcome
Accelerating Materials Development and Deployment
Week 2
Materials Knowledge and Materials Data Science
Week 3
Materials Knowledge Improvement Cycles
Week 4
Case Study in Homogenization: Plastic Properties of Two-Phase Composites
Week 5
Materials Innovation Cyberinfrastructure and Integrated Workflows
FAQ
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
Reviews
Great initiative of creating this course! If you're curious about the idea of combining materials science and data science, this course is for you. Enjoy!
Well presented in a simple manner. Great courses to learn exploratory data in material science and engaging with current issues.
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
the course is nice and useful, but is very tough. You require a good knowledge of statistics, computation, and material science to make it through it.
