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

179 calificaciones
55 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


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


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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26 - 50 de 55 revisiones para Materials Data Sciences and Informatics

por Naveen s

Jun 06, 2020

Very good experience and have learnt allot

por Herbaut J P M

Jul 15, 2019

Great expérience !

Herbaut Julien / Yale

por Jorge A A L

May 29, 2020

It is a intermediate/advanced course

por Prakhar C T

Jun 23, 2020

Very useful course

por Siva S

Jan 12, 2020

Excellent course!

por mansi g

Jul 17, 2018

its easy to do it

por Sheikh N

Oct 10, 2018

Very nice course

por Dr. K R

Mar 17, 2019

Awesome Course!

por Salim A

Dec 18, 2016

very beneficial

por LIM Z H M

Jun 24, 2020

Great course!

por Dr. C K

Jun 14, 2020


por kavuri v

Apr 18, 2020


por Gilbert L

Jan 17, 2020


por Sumit B

Jun 08, 2020

Pretty advaced stuff! The starters must have a solid grip on statistics, Linera algebra(Eigenvalue, Eigenvector, SVD), ,Intergral transforms (Fourier and Laplace), ICT, Computer programming (especially Python) and Introductory materials science. A tensor analysis and Perturbation theory background is helpful.

A lot of new formalism and a good link or repositories have been provided. The n-point statistics and specially the mathematics of Localization are extremely complicated, and poorly presented (localization-homogenization, specially Capital Gamma function and numerical solution to integral equations) of having rich assemblage of knowledge.

The first two weeks and specially the first week could have been arranged in mor pedagogically suitable manner. Still I am Giving it 4 instead of e stars for profound knowledge embedded into the course.

por Yeshar H

Sep 21, 2016

Great, fantastic information that made me see the importance of data sciences in materials science and engineering. My only request would be to potentially spend more time fleshing out PCA and the statistical tools around it; most of it went over my head without seeing a step-by-step application of it that showed the calculations. Maybe it could be optional so that those who are already strong in PCA can skip it.

por Lim J H

Jun 24, 2020

Great concepts and descriptions, however, it can be surprisingly dry and not helping is the monotonous way the lessons are being carried out. The PyMKs helps to alleviate the boredom though so do download the program and try it out for yourself after understanding the basics of the course.

por Zisheng Z

Apr 30, 2018

A great introductory course into Material Data Sciences and Informatics. Had a relatively hard time when the course turned form introduction into hardcore statistics. Moreover, it can be more helpful if there are more practical projects and tutorial on introduced tools.

por Priyabrata D

Apr 29, 2020

Some lectures from week 1 and week 5 are identical, hence repetitive. The case study is really good. Week 3 contains the most important information. Hence, week 3 needs more clarification on a basic level. Sometimes I felt unconnected with the lectures.

por Sashanka A

Jul 03, 2020

This course provides great inputs on how data science can be implemented in material science. Though it didn't deal deep into all the concepts, it was focussed to explain briefly what is out there in the field of materials informatics.

por Navneeth R

May 02, 2020

Overall it was a very good course and I recommend it for all students interested in material science.But the installation procedure could have been updated and I still face problems in installation of Softwares to use.

por Pranav K

May 13, 2020

Good theory lessons. There should have been more focus on utilising software (PyMKS) to implement concepts, throughout the course rather than just the end

por Biplab B

Mar 28, 2020

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.

por Veronica M T

Apr 26, 2020

The course is great but sometimes it was entirely too wordy.

por SAI S S

Mar 04, 2020

Pretty difficult for a beginner / Undergraduate

por Javier G M

Jun 05, 2020

Not bad, but it would be better with a bit of hands-on practice.