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Opiniones y comentarios de aprendices correspondientes a Materials Data Sciences and Informatics por parte de Instituto de Tecnología de Georgia

4.4
estrellas
184 calificaciones
57 revisiones

Acerca del Curso

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....

Principales revisiones

RR

Sep 23, 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

DG

Apr 28, 2020

This course is very much interesting and i have learned about micro structure analysis using data sciences simulation, regression ,finding mechanical properties etc

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1 - 25 de 56 revisiones para Materials Data Sciences and Informatics

por Yichi W

Nov 18, 2016

Too much introduction, not much actual useful stuff. Too much mathematically without well illustrated examples.

por Justin F

Jul 15, 2017

Useful introduction to vocabulary and concepts in the field, but can't help but feel the pacing and scope of the course takes an abrupt switch at times.

por Клявинек С С

Jul 08, 2019

I think it's wonderful course, but I did not have enough real practical skills from it (in my opinion). Thank you very much to the instructors for this course!

por Kevin Y J L

Apr 22, 2019

An excellent introduction to Material informatics. I highly recommend to any beginners to get started with learning informatics regarding materials.

por Pratik K

Oct 25, 2017

Excellent course if you are looking to understand how to design high performance materials leveraging current advances in data sciences.

Very well delivered by Dr. Surya Kalidindi and Prof McDowell. Reference to the book on the subject by Dr. Kalidindi supplemented by web search was useful.

Need to put the new skills acquired, in practice at work, where I see a huge potential.

Thanks Georgia Tech!!

por ANUPAM P

Dec 07, 2017

Very valuable course for materials modelling enthusiast. It provides me the firm grounding and preparation for my future research work in this material modeling. This course is a fine balance of technical knowledge, its implementation and the practical approaches one needs to adopt to effectively use this knowledge of materials modeling in real world. (Anupam Purwar)

por Rushikesh R

Sep 23, 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

por Abdullah A

Aug 18, 2019

The course was overall good but some of the course content is outdated (installing PyMKS) please look into this matter.

por Bernard W

May 04, 2018

Great introduction of the why and how of materials informatics!

por stefan b

Feb 24, 2017

This is a great starter course for materials informatics. It covers a good amount of topics and uses a nice case study to reinforce digital representation of data, spatial correlations, principal component analysis, and regression. I really liked the examples of pyMKS. My only suggestions is it would have been nice to have more hands-ons use of pyMKS and sci-kit learn. This could have been accomplished through a course project or homeworks.

por Thaer M

Sep 21, 2017

This course discussed one particular issue in materials informatics. I hoped to see several other informatics-based techniques to solve problems in materials innovation.

por Lidiya P K

Jun 01, 2020

The course has been very helpful in forming a basic understanding of data sciences application in Materials Engineering. Also it motivated me to explore even more, study and adopt these skills in my research.

In my opinion, a few more lectures on PyMKS applications in the last week would be of more help.

I strongly recommend setting up an advanced followup of this course with deeper analysis and some hands-on practice.

My heartfelt thanks to Prof. Kalidindi for this initiative.

por Zack P

Apr 02, 2020

I am in the process of transitioning from a purely design position to a professional materials engineer for a 3D house printing company. This course was a great fundamental introduction to materials processing history all the way to current high-end cyberinfrastructure like e-collaborative data pipelines, open-source machine learning libraries in python used to make cutting edge material breakthroughs today.

por Ongwenqing

Jun 18, 2020

This course is very informative and relevant for Material Engineering students like me to incorporate Data Science and modern technology to speed up research on the discovery of new materials. This course has also provided useful computational tools such as Pymks. Pymks enable use to compute the 2 point spatial correlation and visualization does help in the analysis of the material's structure properties.

por Mohammed S

Jun 11, 2020

Very informative course. Cover many concepts of data science as well as the Material design field.

I would recommend this course to the people who want to stay in their core field while utilizing modern-day techniques such as machine learning and data science in their work.

por Yiming Z

Jul 19, 2017

Thank you for the course. It is very helpful for my deeper understanding of Materials Informatics. I hope I can get more knowledge and assistance from Professors for my research in this field in future. Thank you!

por DHARMALINGAM G

Apr 28, 2020

This course is very much interesting and i have learned about micro structure analysis using data sciences simulation, regression ,finding mechanical properties etc

por Dhanush S B

May 11, 2020

A perfect course if one wants to pursue a research career in material science with an engineering background.

por Fekadu T B

Jun 01, 2020

You will learn four paradigms of science: empirical, theoretical, computational, and data-driven.

por Gusti U N T

May 17, 2020

Excellent experience. It engages my knowledge broadly about Data Science in Materials. Thank you

por pradeep s c

Jun 01, 2020

It includes ausam information in structured manner to learn the subject easily.

por Madhuri C D

May 22, 2019

Best way to learn newly developed system using material data science.

por LOH X Y

May 18, 2020

Skills on the Data Sciences can be applied to other areas of studies

por Santosh B M

Apr 08, 2020

Good to know about the basics of materials data.

por Anshuman S

Aug 09, 2016

Brilliant lectures on a very interesting topic!