Materials Data Sciences and Informatics

Georgia Institute of Technology via Coursera

Go to Course: https://www.coursera.org/learn/material-informatics

Introduction

### Course Review: Materials Data Sciences and Informatics on Coursera #### Overview The course **"Materials Data Sciences and Informatics"** offered on Coursera is an essential educational endeavor for anyone intrigued by the innovative field of Materials Informatics. Bridging the worlds of materials science, computational science, and information science, this course addresses the rapidly evolving methodologies aimed at accelerating the discovery and implementation of new materials. As a participant, you will dive deep into a discipline that holds the promise of transforming materials development, emphasizing the importance of data-driven approaches at the intersection of these fields. #### Course Content and Structure The syllabus is well-structured and thoughtfully designed, spanning several comprehensive modules that cater to both novices and professionals keen on enhancing their knowledge base. Here’s a breakdown of what to expect: 1. **Welcome**: A brief introduction to set the stage and highlight prerequisites for success. 2. **Accelerating Materials Development and Deployment**: This module reflects on historical paradigms of advanced materials and stresses the necessity for novel strategies integrating data sciences and informatics. You'll learn about important 21st-century initiatives that promise a transformative impact on materials innovation. 3. **Materials Knowledge and Materials Data Science**: By delving into the concepts of property, structure, and process spaces, you'll grasp the essence of Process-Structure-Property linkages. This module opens your eyes to how data science enriches materials knowledge systems. 4. **Materials Knowledge Improvement Cycles**: Here, learners explore how material structure can be digitally represented, the significance of two-point statistics, and the power of Principal Component Analysis in reducing dimensionality. The concepts of Homogenization and Localization are vital in understanding materials at different scales. 5. **Case Study in Homogenization: Plastic Properties of Two-Phase Composites**: This practical application helps consolidate your understanding of homogenization within the context of real-world materials, demonstrating theoretical principles through analysis of two-phase composites. 6. **Materials Innovation Cyberinfrastructure and Integrated Workflows**: The final module delves into contemporary materials innovation systems and the infrastructure supporting them. This section covers the essentials of materials databases, e-collaboration platforms, integrated workflows, and metadata handling, which are crucial for effective data management and collaboration in research. #### Review and Recommendations **Pros**: - **Interdisciplinary Approach**: The course effectively integrates concepts from various domains, providing a holistic view of Materials Informatics. - **Cutting-Edge Content**: It addresses the pressing need for new data-driven methods in materials science, keeping learners informed on the latest trends and tools. - **Practical Applications**: The inclusion of case studies enhances the learning experience, allowing participants to apply theoretical concepts in tangible contexts. - **Accessible Learning**: The course is structured in a progressive manner, suitable for individuals at different levels of expertise. **Cons**: - **Time Commitment**: Material covered can be dense, which may require a significant time investment to grasp thoroughly. - **Technical Proficiency**: Some modules may necessitate a basic understanding of programming or data analysis for deeper comprehension. #### Conclusion If you are passionate about advancing in the fields of materials science or data science, **"Materials Data Sciences and Informatics"** is highly recommended. This course offers a timely exploration of the pivotal role of data in materials innovation and equips you with the knowledge to actively engage in this emerging field. By the end of the course, you will not only enhance your understanding of materials development cycles but also find yourself better positioned to contribute to next-generation materials research and applications. Enrollment in this course represents a valuable investment in your professional development, opening doors to both academic and industry opportunities in the dynamic landscape of Materials Informatics.

Syllabus

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

Materials Innovation Cyberinfrastructure and Integrated Workflows

• Learn about materials innovation system and cyberinfrastructure • Review Materials Databases, e-collaboration platforms and code repositories • Learn why integrated workflows are needed • Define Metadata, Structured and Unstructured data • Learn about available services for e-collaborations

Overview

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

Skills

Informatics Materials Statistics Data Science

Reviews

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.

A good summary of the present challenges and need for Active learning and advanced ways of material development by leveraging the data and physics

Excellent course. I thoroughly enjoyed the instructor's style of teaching. Thanks for making the concepts of material informatics very clear to me.

It is a great way to combine both the branches, Material sciences, and data science. I completely loved this certification. Looking forward to learning more.