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Вернуться к Materials Data Sciences and Informatics

Отзывы учащихся о курсе Materials Data Sciences and Informatics от партнера Технологический институт Джорджии

Оценки: 296

О курсе

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....

Лучшие рецензии


22 сент. 2018 г.

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


27 апр. 2020 г.

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

Фильтр по:

26–50 из 77 отзывов о курсе Materials Data Sciences and Informatics

автор: Siddhalingeshwar I G

8 сент. 2020 г.

I take this opportunity to express sincere gratitude to Dr Surya Kalidindi. Thank you COURSERA yet again.

автор: Fekadu T B

1 июня 2020 г.

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

автор: Gusti U N T

17 мая 2020 г.

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

автор: SILVANA C C

13 нояб. 2020 г.

Thank you, Teacher!! It is amazing course and I improve my knowledge and skills in this field!!

автор: Pradeep S

1 июня 2020 г.

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

автор: Li J Y

23 авг. 2020 г.

Interesting content! Liked the explanation of principle component analysis.

автор: Madhuri C D

22 мая 2019 г.

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

автор: LOH X Y

18 мая 2020 г.

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

автор: Youxing C

4 окт. 2020 г.

It exactly fits my needs for this area. Highly recommended!

автор: Santosh B M

8 апр. 2020 г.

Good to know about the basics of materials data.

автор: Anshuman S

9 авг. 2016 г.

Brilliant lectures on a very interesting topic!

автор: Naveen s

6 июня 2020 г.

Very good experience and have learnt allot

автор: Herbaut J P M

15 июля 2019 г.

Great expérience !

Herbaut Julien / Yale

автор: Jorge A A L

29 мая 2020 г.

It is a intermediate/advanced course

автор: Marcin F

11 авг. 2020 г.

Excellent presentation and content

автор: Prakhar C T

23 июня 2020 г.

Very useful course

автор: Sivaprakash S

12 янв. 2020 г.

Excellent course!

автор: mansi g

17 июля 2018 г.

its easy to do it

автор: Deleted A

10 окт. 2018 г.

Very nice course

автор: Dr. K R

17 мар. 2019 г.

Awesome Course!

автор: Salim A

18 дек. 2016 г.

very beneficial

автор: LIM Z H M

24 июня 2020 г.

Great course!

автор: paul g

7 апр. 2021 г.


автор: Mona A A

10 июля 2020 г.


автор: Dr. C K

14 июня 2020 г.