Materials Informatics
Hands-On Tutorials
A lecture series that takes you from zero to writing Python code that queries million-entry materials databases and trains machine learning models. No prior materials science required.
Before You Start
You should know how to write basic Python: variables, loops, functions, and how to install a library with pip. If you have never used Python before, complete a free beginner course first (freeCodeCamp or CS50P are excellent).
You need a way to run Python notebooks. The easiest option is Google Colab. It runs in your browser with no installation. Alternatively, install Jupyter locally with pip install jupyter.
High-school level algebra is enough. You do not need calculus or linear algebra to follow these lectures, though those will help you go deeper later.
No prior materials science knowledge needed. Each lecture explains the domain concepts before writing any code. If you are curious why a material conducts electricity or why steel is strong, you are ready.
Lessons
Python for Materials Databases
The basics of materials informatics, from scratch. You will learn what materials databases are, why researchers built them, and how to write Python code that queries millions of materials in seconds. The lesson covers the six major databases (Materials Project, AFLOW, OQMD, COD, NOMAD, ICSD), the Python libraries that talk to them (mp-api, pymatgen, matminer), and ends with a full band-gap prediction pipeline you can run yourself. No prior materials science required. Every concept is explained before any code is written.