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

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!

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.

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

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!!

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)

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

The course was overall good but some of the course content is outdated (installing PyMKS) please look into this matter.

Great introduction of the why and how of materials informatics!

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.

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

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.

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.

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!

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

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

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

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

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

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

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

Good to know about the basics of materials data.

Brilliant lectures on a very interesting topic!

Great expérience !

Herbaut Julien / Yale

It is a intermediate/advanced course