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Materials Data Sciences and Informatics に戻る

ジョージア工科大学(Georgia Institute of Technology) による Materials Data Sciences and Informatics の受講者のレビューおよびフィードバック

4.4
195件の評価
59件のレビュー

コースについて

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....

人気のレビュー

VV

Jul 28, 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.

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

フィルター:

Materials Data Sciences and Informatics: 51 - 58 / 58 レビュー

by Veronica M T

Apr 26, 2020

The course is great but sometimes it was entirely too wordy.

by SAI S S

Mar 04, 2020

Pretty difficult for a beginner / Undergraduate

by Javier G M

Jun 05, 2020

Not bad, but it would be better with a bit of hands-on practice.

by Xin L

Dec 30, 2019

interesting class

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 Rachel H

May 20, 2020

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

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 Shijie Z

Aug 27, 2017

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