Quant Academy
A complete, self-contained, interactive pathway from foundational mathematics to professional-level quantitative finance, built on evidence-based learning science and runnable entirely offline.
Those who seek power may become electricians.
Those who seek wisdom may become librarians.
But those who would master the laws that bind us all must become quants.
Complete these lessons, and here thou shalt find knowledge, and power enough to rival mine.
Curriculum
How this academy teaches
Learn by doing, not reading
Every lesson runs on evidence-based methods: closed-book retrieval, spaced flashcards, interleaved exams, prediction gates, and error logs. See Phase 0.
Real math, real code
Formulas render locally with KaTeX; Python runs for real in a sandboxed, offline Pyodide worker (numpy/scipy/pandas). Interactive workbenches let you manipulate every core object - from secant lines to Brownian paths to volatility surfaces.
Rigorous and honest
Definitions, theorems, proofs, and worked derivations, cross-checked for accuracy. We distinguish theorem from intuition, approximation from equality, and make no claims about trading profitability.
Offline & private
No accounts and no login; your progress lives in your browser’s local storage (export/import to back it up), and the full math + Python runtime is bundled locally. This public site adds privacy-respecting, IP-anonymised analytics (see the privacy note).
Project Euler Lab
997 computational problems, mapped to the curriculum, with a Python workbench, hint ladders and mastery tracking.
Study tools
Help Improve Quant Academy
Spot an error, a broken feature, a wrong answer, or a typo? Report it or suggest a correction. Always free, no account needed.