Quant Science drops hands‑on tutorials

Quant Science pushed runnable Python notebooks and a downloadable "Quant Scientist Algorithmic Trading System" to their Learn site and public repos, explicitly packaging an end‑to‑end hedge‑fund workflow for reuse in Jupyter case studies (learn.quantscience.io). (learn.quantscience.io) Their GitHub org lists three public repositories (including vectorbt_backtesting and zipline_backtesting), shows ~922 followers, and records zipline_backtesting and vectorbt_backtesting updates dated July 1, 2024 and November 7, 2023 respectively—files are delivered as Jupyter/Python notebooks suitable for reproducible backtests (github.com). (github.com) Quant Science identifies founders Jason Strimpel and Matt Dancho on course pages and markets a paid "QS Pro" program that claims outperformance from 2022–2025 and reports training "350+ Python enthusiasts" in its algorithmic trading system materials (learn.quantscience.io). (learn.quantscience.io) The creator channel published a multi‑part YouTube series titled "I Built An End‑to‑End Quant Hedge Fund In Python" (parts posted across 2025–2026), with individual episodes showing data pipelines, risk controls and overnight backtests and drawing tens of thousands of views on some installments (youtube.com). (youtube.com) Their newsletter and blog publish hands‑on machine‑learning tutorials (for example, an autoencoder‑based feature‑embedding walkthrough) and explicitly supply downloadable code and notebooks alongside the lessons (quantscience.io). (quantscience.io) Course pages and marketing emphasize live workshops, an active Discord community, and a waitlist for full course access, while site content and tutorials include an explicit educational disclaimer stating the material is for instruction and not financial advice ( ). (quantscience.io)