MSE 591 602 Introduction to Materials Informatics

1 Credit Hours

The 8-week course is designed to introduce hands-on Materials Informatics (MI) concepts, where the students can onboard data science skills and directly see the implications of their analysis on a systematic process of inquiry. The course consists of 6 interactive modules on data science topics. First three modules cover general Data Science concepts like Data, Big data, Data gathering, handling and Data analysis. The hands-on part allowed to develop skills of data handling in Jupiter notebook, gain basics of Python, familiarize students with working in Anaconda Navigator environment. The second part is dedicated to Machine Learning concepts. Particularly, general overview of Unsupervised, Supervised Learning is accompanied by representative methods (like K-means and SVM) and approaches applied to the sample dataset. Each module consists of 1-hour lecture on topic materials, paired with a hands-on video and practice module activity. After completing the module, students are offered to work independently on self-learn tasks.

 

Updated: 10/31/2022