Algo‑trading learning resources surfaced

Algorithmic trading — using code to turn trading rules into automatic buy and sell orders — is getting a fresh wave of beginner material, from GitHub lists to live Python workshops. (github.com) (learn.quantscience.io) One of the biggest public directories is the GitHub project “best-of-algorithmic-trading,” which says it tracks 100 open-source projects across seven categories, including bots, libraries, books, courses, and communities. The repository was updated for version 2026.03.26 three weeks ago. (github.com) That list ranks Freqtrade as its top bot and framework, and Freqtrade’s own GitHub page describes it as a free, open-source crypto trading bot with about 48,900 stars, 10,200 forks, and commits as recently as three days ago. (github.com 1) (github.com 2) Backtesting is the core skill behind most of these materials: it means running a strategy on old market data to see how it would have behaved before risking real money. Quant Science says its training teaches both vector-based and event-based backtesting frameworks, the two common ways Python traders simulate portfolios and orders. (quantscience.io) (learn.quantscience.io) Quant Science is pitching that process directly to newcomers. Its registration page advertises a live “Algorithmic Trading Workshop” for Thursday, April 30 at 10:00 a.m. Eastern time and says the session will cover 15 algorithmic trading skills. (learn.quantscience.io) A follow-up page for registrants says the workshop is capped at 500 seats and tells attendees to join five minutes early because the event can fill up. The same page says more than 425 traders, quants, and beginners have joined the course series. (learn.quantscience.io) The workshop is part of a larger education business built by Jason Strimpel and Matt Dancho. Quant Science’s about page says Strimpel previously worked in quantitative and trading roles at JPMorgan Chase, TradeGroup, BP Trading, Rio Tinto, and Amazon Web Services, and says Dancho co-founded the project with him in 2022. (quantscience.io) (learn.quantscience.io) The pitch is not just education. Quant Science’s pages promise “profitable trading strategies,” while its paid products range from a $497 backtesting course to higher-ticket systems that bundle live clinics, software, and community access. (learn.quantscience.io 1) (learn.quantscience.io 2) (learn.quantscience.io 3) That matters in a corner of finance where open-source code and paid coaching now sit side by side. On the same web, a newcomer can pull a free bot from GitHub, browse a ranked resource list, and then get funneled into a live sales-and-training event built around Python trading systems. (github.com 1) (github.com 2) (learn.quantscience.io) The next marker is April 30. By then, the latest burst of algo-trading content will have moved from shared links and sample code to a live classroom with a 500-seat clock on it. (learn.quantscience.io) (learn.quantscience.io)