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

310 calificaciones

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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 reseñas


22 de sep. de 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


27 de abr. de 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 78 revisiones para Materials Data Sciences and Informatics

por Yichi W

18 de nov. de 2016

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

por Сергей С К

8 de jul. de 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 Justin F

14 de jul. de 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 Stefan B

24 de feb. de 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 Kevin Y J L

21 de abr. de 2019

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

por Pratik K

25 de oct. de 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!!


6 de dic. de 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

22 de sep. de 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

18 de ago. de 2019

The course was overall good but some of the course content is outdated (installing PyMKS) please look into this matter.

por Bernard W

4 de may. de 2018

Great introduction of the why and how of materials informatics!

por Sae D

21 de sep. de 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

1 de jun. de 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

2 de abr. de 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

18 de jun. de 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 Yassine F

8 de sep. de 2020

Thanks a lot for this clear and efficient MOOC! I look forward to learning more about the topic. I'll try to find time to read the examples on the pymks web site. Thanks Mr Kalidindi and all the staff!

Best Regards!

Yassine Ferchichi, University Teacher (Tunisia Private University - Mechanical Engineering Department)

por Mohammed S

11 de jun. de 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 Emmanuel E

29 de mar. de 2022


por Yiming Z

19 de jul. de 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 Victor V d C P

28 de jul. de 2020

It's a great course that can give you a wide view of how to accelerate the development of material using computational resources. I'm a Metallurgical Engineer and I totally recommend this course.


28 de abr. de 2020

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


8 de oct. de 2020

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.

por Luis A G R

18 de jul. de 2020

Great initiative of creating this course! If you're curious about the idea of combining materials science and data science, this course is for you. Enjoy!

por uttam r L

18 de feb. de 2022

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

por M L M

11 de nov. de 2020

Well presented in a simple manner. Great courses to learn exploratory data in material science and engaging with current issues.

por Dhanush S B

11 de may. de 2020

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