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100+ beginner-friendly chapters with code that runs in your browser. No setup. No accounts. Built by engineers, for engineers.

tutorial.py
# Try this in your browser β†’
from sklearn.linear_model import LinearRegression
import numpy as np

X = np.array([[1],[2],[3],[4]])
y = np.array([2, 4, 6, 8])

model = LinearRegression().fit(X, y)
print(model.predict([[5]]))
# β†’ [10.]
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Runs in your browser

Every Python snippet has a β–Ά Run button β€” powered by Pyodide. No installation, no accounts. Just click and execute.

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Truly beginner-friendly

Every chapter starts with the mental model + a diagram. Plain English first, then code. No jargon you can't decode.

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Real production patterns

Minimal example to get it working, then the real-world version with validation, error handling, edge cases.

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Built-in recall tests

Every chapter ends with flashcard-style Q&A. Quiz yourself before moving on β€” answers reveal on click.

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Mermaid diagrams in every chapter. Click to zoom. Architecture, request flow, state machines β€” explained visually.

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