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學生對 乔治亚理工学院 提供的 Materials Data Sciences and Informatics 的評價和反饋

4.5
280 個評分
74 條評論

課程概述

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....

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VV
2020年7月27日

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.

RR
2018年9月22日

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

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1 - Materials Data Sciences and Informatics 的 25 個評論(共 74 個)

創建者 Yichi W

2016年11月18日

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

創建者 Сергей С К

2019年7月8日

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!

創建者 Justin F

2017年7月14日

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.

創建者 Stefan B

2017年2月24日

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.

創建者 Kevin Y J L

2019年4月21日

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

創建者 Pratik K

2017年10月25日

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!!

創建者 ANUPAM P

2017年12月6日

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)

創建者 Rushikesh R

2018年9月22日

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

創建者 Abdullah A

2019年8月18日

The course was overall good but some of the course content is outdated (installing PyMKS) please look into this matter.

創建者 Bernard W

2018年5月4日

Great introduction of the why and how of materials informatics!

創建者 Sae D

2017年9月21日

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

創建者 Lidiya P K

2020年6月1日

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.

創建者 Zack P

2020年4月2日

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.

創建者 Ongwenqing

2020年6月18日

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.

創建者 Ferchichi Y

2020年9月8日

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)

創建者 Mohammed S

2020年6月11日

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.

創建者 Yiming Z

2017年7月19日

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!

創建者 Victor V D C P

2020年7月28日

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.

創建者 DHARMALINGAM G

2020年4月28日

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

創建者 PRIYANSHI C

2020年10月8日

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.

創建者 Luis A G R

2020年7月18日

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!

創建者 Muhammad L M

2020年11月11日

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

創建者 Dhanush S B

2020年5月11日

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

創建者 Siddhalingeshwar I G

2020年9月8日

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

創建者 Fekadu T B

2020年6月1日

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