Free algo-trading course

Quant Science is pitching a free Python course and live workshop as an on-ramp for beginners who want to build rule-based trading systems. (learn.quantscience.io) The live session is scheduled for Thursday, April 30, at 10:00 a.m. Eastern, and the registration page says it will cover 15 algorithmic-trading skills. The same page says seats are capped at 500. (learn.quantscience.io) A separate Quant Science workshop page says attendees will get two free downloads: an “Algorithmic Trading System Blueprint” and a “Backtest QA Checklist.” It also says the session will walk through a workflow from data and signals to backtesting, risk, deployment, and monitoring. (learn.quantscience.io) Algorithmic trading means turning a trading idea into coded rules that generate signals and positions automatically. Backtesting means running those rules on historical market data to see how they would have performed before risking real money. (investor.gov, britannica.com) Quant Science’s pitch centers on reproducibility: using the same research pipeline each time so a strategy can be checked, rerun, and compared instead of traded from instinct. Its 2023 framework post breaks that process into strategy formation, backtesting, and live trading, with feedback loops between each stage. (quantscience.io) The company’s public site says its broader paid program is aimed at people learning algorithmic trading with Python in under 60 days. That site says students get core strategies, backtesting frameworks, and a trading-process template. (quantscience.io) The free offer sits at the top of a larger sales funnel. Quant Science’s checkout page lists its main course at $2,499 upfront or three payments of $997, while another course page says the system has taught 350-plus Python enthusiasts and trained 500-plus traders across 12 cohorts. (learn.quantscience.io, learn.quantscience.io, learn.quantscience.io) The appeal is straightforward: many new traders can find charting tips online, but fewer free courses show how to structure data, test ideas, measure drawdowns, and document results in code. Quant Science’s registration pages repeatedly frame the workshop as a way to show that end-to-end process live rather than teach isolated indicators. (learn.quantscience.io, learn.quantscience.io) The catch is also straightforward: a backtest is not a live track record, and regulators routinely warn that hypothetical performance can mislead investors if costs, slippage, and changing market conditions are ignored. The Securities and Exchange Commission’s investor education materials say automated strategies still carry market risk and require understanding of the underlying assumptions. (sec.gov, investor.gov) For beginners, the immediate date to watch is April 30. That workshop is where Quant Science says it will show, live, how a trading idea moves from Python code to a tested strategy. (learn.quantscience.io)