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Six modules. One desk.
181 pages of free, opinionated material on trading automation. Each module ships as a web page and a printable PDF. Read in any order, but the dependency map at the bottom of this page tells you what each module expects from the others.
- MODULES
- 06
- PAGES
- 181
- FORMAT
- WEB·PDF
- PRICE
- $0
// start here
Curriculum Index — the master cross-reference.
A 14-page PDF that explains the reading order, the dependency map between modules, a study guide, an honest limits section, and a glossary of recurring terms.
The six modules.
Each card links to the web page and the PDF for that module.
- // module · 0131 PAGES
Coding Fundamentals
The Python, git, and shell habits the rest of the curriculum assumes.
- Pure functions, side effects on the edges
- Type hints, dataclasses, reading other people's code
- Project structure: src layout, tests, one main.py
- git workflow: branches, PRs, the rare force-push exception
Prereqs · None — start here if you have not written Python recently.
- // module · 0214 PAGES
Platform Coverage
An honest survey of the six platforms most people actually use.
- Where each platform helps and where it traps you
- What 'broker-of-record' really commits you to
- Latency, fees, and data-quality differences that move PnL
- Migration paths between platforms without losing history
Prereqs · None — readable alongside Coding Fundamentals.
- // module · 0336 PAGES
Backtesting
How to design a backtest that does not lie to you.
- Walk-forward, purged k-fold, combinatorial CV
- Look-ahead leaks: the seven varieties and how to catch them
- Survivorship, point-in-time data, corporate actions
- Slippage and fee models that match your venue
Prereqs · Coding Fundamentals; Data Engineering recommended.
- // module · 0428 PAGES
Data Engineering
Bars, ticks, vendors, alignment, and the boring layer everything else rides on.
- Bar construction: time, tick, volume, dollar, imbalance
- Vendor comparison: who covers what, at what cost
- Point-in-time joins and the as-of pattern
- Schema design for a research warehouse
Prereqs · Coding Fundamentals.
- // module · 0540 PAGES
Machine Learning
Models that survive contact with markets — and how to tell which do not.
- Feature engineering for non-stationary data
- Linear, tree, gradient-boost, neural — when each wins
- Cross-validation that respects time and embargo
- The 15 production gates before going live
Prereqs · Backtesting and Data Engineering.
- // module · 0632 PAGES
Operations, CLI & Recovery
The desk is the system. Procedures, incidents, recovery trees, monitors, gates.
- 10 runbook procedures (deploy, rollback, kill-switch, drill)
- 6 incident classes: detection → containment → postmortem
- 12 monitors across infra, data, model, and PnL
- 20 cadence gates: pre, daily, weekly, monthly, quarterly
Prereqs · All prior modules — operations assumes the system exists.
How the modules connect.
Arrows mean ‘the downstream module assumes you read this’. Modules 02 and 04 are siblings — read them in either order, but before 03.
01 · Coding Fundamentals
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02 · Platform Coverage 04 · Data Engineering
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03 · Backtesting
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05 · Machine Learning
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06 · Operations / CLI / RecoveryModule 03 (Backtesting) is the linchpin. If you skip it, every later module degrades — feature design loses its honesty check, and operations gates lose their backtest baseline to compare against.
Educational only · Trading stocks, options, futures and crypto involves substantial risk of loss and is not suitable for everyone. You can lose more than you invest in leveraged products. Only trade money you can afford to lose. Past performance does not guarantee future results. Nexural is a trading community and publisher. Everything we share is general education and our own trades — the same for every member, not advice tailored to you. We are not a broker-dealer, investment adviser, commodity trading advisor, or commodity pool operator. Do your own research; you trade at your own risk.