Materials Informatics 101¶

Informatics is the use of computational tools (e.g. AI, machine learning) to access and make sense of data. Materials Informatics has the potential to accelerate scientific inquiry and support novel insights. However, informatics tools are typically marketed to the biological sciences, financial sector, and “Big Tech”—it is not immediately clear how to use “cat-detector technology” to support serious materials science!

The materials on this site are part of a hands-on workshop aimed at training material scientists to use programming-based informatics tools. In this workshop, you will create reproducible data workflows, automate tedious data extraction, visualize data for exploration, and apply AI/ML models for their predictive capabilities.

Wellesley 2022 Workshop¶

This is the schedule for MI 101 at Wellesley in March of 2022.

	Date	Topics	Notebooks	Slides
1	Thursday, March 17	Introduction, data extraction	00 (Day)	Day 1
		Python introduction	01 (Day)
		Data wrangling and tidy data	02 (Day)
	(Take-home)	Programmatic data management	03 (Take-home)
2	Friday, March 18	Principles of visualization	(Activity)	Activity Slides
		Visualizing with plotnine	04 (Day)	Day 2
		ML Fundamentals	05 (Day)

Past Offerings¶

See the Past Offerings page for information on prior runs of this workshop, including recordings and slides.

Binder Option for Broken Python Installation¶

If you haven’t managed to get your python installation working, use the following link to launch the materials in a cloud-based environment:

Be warned that you cannot save your work in Binder!

About the Author¶

Zach del Rosario is on the faculty at Olin College. He helps scientists and engineers reason about uncertainty.

Materials Informatics 101