Georgia Tech - Materials Data Sciences and Informatics
- Offered byCoursera
- Public/Government Institute
Materials Data Sciences and Informatics at Coursera Overview
Duration | 9 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Materials Data Sciences and Informatics at Coursera Highlights
- Earn a shareable certificate upon completion.
- Flexible deadlines according to your schedule.
Materials Data Sciences and Informatics at Coursera Course details
- 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 at Coursera Curriculum
Welcome
Course Syllabus
Frequently Asked Questions
Suggested Reading
Target Audience and Recommended Background
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Why Accelerate Material Discovery and Development?
Historical Materials Development Cycles
How do we accelerate materials development and deployment
Emergence of multi-stakeholder initiatives
The Materials Innovation Ecosystem
Part 1:Multiscale Modeling and Multilevel Design of Materials
Part 2: Multiscale Modeling and Multilevel design of Materials
Decision-Making in Material Design
Multilevel Systems-Based Materials Design
Earn a Georgia Tech Badge/Certificate/CEUs
Accelerating Materials Development and Deployment
Materials Knowledge and Materials Data Science
Material Property, Material Structure, and Manufacturing Processes
Process-Structure-Property (PSP) Linkages
Role of Structures in PSP Linkages
Data Science Terminology
Main Components of Data Science
What is Big Data?
Materials Knowledge and Materials Data Science
Materials Knowledge Improvement Cycles
Digital Representation of Material Structure
Spatial Correlations: n-Point Statistics
Computation and Visualization of 2-Point Spatial Correlations
Principal Component Analyses (PCA) for low dimensional representations
Principal Component Analyses (PCA) for low dimensional representation of material structure
Homogenization: Passing Information to Higher Length Scales
Materials Knowledge Improvement Cycles
Case Study in Homogenization: Plastic Properties of Two-Phase Composites
Structure-Property Linkages using a Data Science Approach-Part 1
Structure-Property Linkages using a Data Science Approach-Part 2
Case Study in Homogenization: Plastic Properties of Two-Phase Composites
Materials Innovation Cyberinfrastructure and Integrated Workflows
Materials Innovation Ecosystem
Materials Innovation Cyberinfrastucture
e-Collaboration Platforms/Environments
Materials Cyber-Infrastructure
Introduction to PyMKS Materials Knowledge Systems in Python
Materials Data Science with PyMKS
PyMKS website
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Materials Innovation Cyberinfrastructure and Integrated Workflows
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