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.






Thursday, March 17

Introduction, data extraction

00 (Day)

Day 1

Python introduction

01 (Day)

Data wrangling and tidy data

02 (Day)


Programmatic data management

03 (Take-home)


Friday, March 18

Principles of visualization


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: Binder

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.