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Learner Reviews & Feedback for Materials Data Sciences and Informatics by Georgia Institute of Technology

4.3
102 ratings
25 reviews

About the Course

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....

Top reviews

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

AA

Aug 18, 2019

The course was overall good but some of the course content is outdated (installing PyMKS) please look into this matter.

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1 - 24 of 24 Reviews for Materials Data Sciences and Informatics

By Kevin Y J L

Apr 22, 2019

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

By Yichi W

Nov 18, 2016

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

By Bernard W

May 04, 2018

Great introduction of the why and how of materials informatics!

By Pratik K

Oct 25, 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!!

By Rushikesh R

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

By Abdullah A

Aug 18, 2019

The course was overall good but some of the course content is outdated (installing PyMKS) please look into this matter.

By ANUPAM P

Dec 07, 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)

By stefan b

Feb 24, 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.

By Клявинек С С

Jul 08, 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!

By Thaer M

Sep 21, 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.

By Justin F

Jul 15, 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.

By K. R

Mar 17, 2019

Awesome Course!

By Salim A

Dec 18, 2016

very beneficial

By mansi g

Jul 17, 2018

its easy to do it

By Madhuri C D

May 22, 2019

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

By Herbaut J P M

Jul 15, 2019

Great expérience !

Herbaut Julien / Yale

By Anshuman S

Aug 09, 2016

Brilliant lectures on a very interesting topic!

By Yiming Z

Jul 19, 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!

By Sheikh N

Oct 10, 2018

Very nice course

By Zisheng C 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.

By 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.

By Henry Z

Apr 25, 2018

照本宣科。以及习题的设置,怕不是在开玩笑?

By 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)

By Shijie Z

Aug 27, 2017

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