marimo in the classroom | marimo

🎓 Classes using marimo. See how educators across the world teach with marimo.
From your first line of Python to your first language model. See how educators bring their subjects to life with marimo — on the web with molab or WebAssembly, or on students' own computers.
67 courses at 58 universities in 22 countries.
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We rotate featured courses each term. Browse every course below.
In-class network science labs plus a graded Pair Notebook with a Socratic AI tutor.
Bioinformatics, DNA sequence analysis, and motifs, with exercises on molab.
Design and build Earth Observation apps for object-based image analysis, comparing eCognition, Jupyter, and marimo.
Descriptive, inferential, and Bayesian statistics with in-browser companion notebooks.
Learn fMRI analysis from a marimo-book textbook, with assignments graded on molab.
A marimo-only course on wrangling and analyzing data. Students use molab in the browser.
Protein sequence analysis and protein language models, with projects on molab GPUs.
Build custom data visualizations in Python with anywidget.
Signal detection and estimation theory, taught with lecture notebooks that run in the browser.
Weekly regression and econometrics notebooks, each with a molab link.
Filtering, image processing, and computer vision across 12 notebooks with molab links.
Finite differences and discontinuous Galerkin methods, with exercises graded via mograder.
Sequence alignment, BLAST, and sequence evolution in molab labs and a capstone.
Core econometrics built in marimo and exported to run in the browser.
Explore semiconductor devices through interactive in-browser notebooks.
Build toward training a language model, from neural networks to transformers. Homework co-developed with the marimo team.
Efficient ML and deployment, taught through 34 interactive in-browser labs.
Metrology, calibration, and regression in a marimo-book with Open in molab on every page.
Numerical methods for materials modelling in notebooks students run locally.
Python, geospatial analysis, and hydraulics, ported from Jupyter with in-browser versions.
Gaussian processes, Bayesian neural networks, and uncertainty quantification, graded with mograder.
Semiconductor physics and devices across 26 interactive lecture notebooks.
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