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.
Offered By
Learners taking this Course are
- Chemists
- Researchers
- Scientists
- Technical Solutions Engineers
- Machine Learning Engineers
Syllabus - What you will learn from this course
Welcome
What you should know before you start the course
Accelerating Materials Development and Deployment
• Learn and appreciate historical paradigms of advanced materials development while emphasizing the critical need for new approaches that employ data sciences and informatics as the glue to connect computational simulation and experiments to speed up the processes of materials discovery and development. • Learn about the emergence of key national and international 21st century initiatives in accelerated materials discovery and development and how they are expected to bring about a disruptive transformation of new product capabilities and time to market.
Materials Knowledge and Materials Data Science
• Understand property, structure and process spaces • Learn about Process-Structure-Property Linkages • Learn what does Materials Knowledge mean • Learn about a role of Data Science in Materials Knowledge System • Overview approaches and main components of Data Science • Learn about a new discipline - Materials Data Sciences
Materials Knowledge Improvement Cycles
• Learn material structure and its digital representation • Learn how to calculate 2-point statistics • Learn how Principal Component Analysis can be used to reduce dimensionality • Understand Homogenization and Localization concepts
Case Study in Homogenization: Plastic Properties of Two-Phase Composites
This module demonstrates a homogenization problem based on an example of two-phase composites
Top reviews from Materials Data Sciences and Informatics
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 was overall good but some of the course content is outdated (installing PyMKS) please look into this matter.
Instructor
Dr. Surya Kalidindi
ProfessorAbout Georgia Institute of Technology
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
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.
What is the refund policy?
Is financial aid available?
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