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

4.3
estrellas
147 calificaciones
43 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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26 - 45 de 45 revisiones para Materials Data Sciences and Informatics

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 K. R

Mar 17, 2019

Awesome Course!

por Salim A

Dec 18, 2016

very beneficial

por kavuri v

Apr 18, 2020

good

por Gilbert L

Jan 17, 2020

nice

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 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 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 Xin L

Dec 30, 2019

interesting class

por CEDRIC T

Dec 04, 2019

The course gives a "good" overview of some techniques but is way too descriptive, way too theoretical. There is no progressive (computational) practice. The major flaws of this course are: 1)no handouts of the slides provided, 2) reference to papers are not clickable URL's, 3) PyMKS runs in Python 2.7 (not 3.4) with many modules deprecated. Running this PyMks is therefore not easy at all and bugged with the environments. Once you get in the course is just about replicating some logic without going in-depth of the potential of this tool. As well , what are more up to date tools to be used? 5) instructors are not really good at teaching , 6) there is no active learners community at this period (november 2019)

por Rachel H

May 20, 2020

It took until the last 15 minutes of week 5 to get to the actual data science...

por Henry Z

Apr 25, 2018

照本宣科。以及习题的设置,怕不是在开玩笑?

por Shijie Z

Aug 27, 2017

Too much talk about general idea. Lack of practice to learn skills