04Foundation course

Certified AI Trading Explorer

A platform-neutral, myth-busting guide to automated and AI trading: telling rules-based bots from machine-learning models from AI-assisted tools, understanding how grid, DCA, arbitrage, signal and copy bots really work and fail, evaluating trading signals, backtesting and forward-testing honestly, recognising overfitting and black-swan fragility, and setting the risk controls and API-key safeguards every automated strategy needs before real capital.

6 modules

~30 min20-question exampass 70%

01What AI and Algorithmic Trading Actually Mean"AI trading" is marketing shorthand for three very different things; learn to tell a rules-based bot from real machine learning from an AI-assisted tool, and most of the hype falls away.
02Types of Trading BotsAlmost every trading bot is one of five types, and each one has a market condition where its edge quietly turns into a loss.
03How Trading Signals WorkA trading signal is an instruction to buy or sell produced by a defined method; learn the three families of signals, how sellers really make money, and how to check a source before you trust it.
04Backtesting and Forward TestingA backtest shows how a strategy would have done on the past; forward testing proves it on live data, and live results are almost always worse than the backtest promised.
05Risks of AI Trading: Overfitting and Black Swan EventsOverfitting makes a strategy look brilliant on old data and useless on new, and a black swan is the rare shock no bot was built for, which is why a human keeps a hand on the off-switch.
06Risk Controls for Automated StrategiesA bot without hard, pre-set limits is an unbounded liability, so set the kill switch, sizing caps, API-key rules, and monitoring before it ever touches real money.