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SciPy

Optimisation, integration, statistics and signal processing.

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This course has 3 lessons. Start with the first one and use the next / previous links at the bottom of each lesson — the sidebar keeps the whole course in order.

Lessons

  1. SciPy arrays and NumPy interopHow SciPy relates to NumPy, what it adds on top of the array type, and how to keep a large problem sparse instead of dense.
  2. Optimisation and curve fittingminimize for general problems, curve_fit for a model fitted to data, and how to tell a real solution from a local one.
  3. Statistics and signal processingscipy.stats for distributions, fitting and hypothesis tests; scipy.signal for filter design, zero-phase filtering and peak detection.

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Last refreshed 2026-09-17.