Foundations of Algorithmic Trading
What algorithmic trading really is, how markets and orders actually work, the anatomy of a trading system, and the end-to-end workflow you will use for the rest of the course.
Your AI Copilot: Building Bots with AI
You are not learning to code alone. This part shows you how to use an AI assistant as a tutor and pair-programmer to learn faster and build trading bots — and, crucially, how to verify what it gives you so it never blows up your account.
Your Toolkit: Python & Market Data
Set up a professional Python trading environment, pull clean OHLCV data from real sources, wrangle it in pandas, compute the core indicators from scratch, and validate the data before you ever trust a backtest.
Designing a Trading Strategy
Turn a market hypothesis into precise, codeable rules — what a real edge is, the trend, momentum and mean-reversion archetypes in working Python, filtering signals by regime, and the exits and trade management that actually decide your returns.
Building a Backtester in Python
Build a vectorised backtester from scratch, measure it honestly with Sharpe and drawdown, layer in realistic costs, then graduate to an event-driven engine and a full backtesting library.
Backtesting Pitfalls & Robustness
The honest part of the course: how backtests lie to you — overfitting, look-ahead and survivorship bias — and the disciplines that catch the lie before it costs you money: train/test splits, walk-forward analysis, Monte Carlo and parameter stability.
Risk & Money Management
The real edge is survival. Position sizing, fixed-fractional and volatility-targeted risk, the Kelly criterion, stops, take-profits and portfolio heat — the maths that keeps you in the game, all in runnable code.
Building a Live Python Trading Bot
Take a strategy off the backtest and into the world: the architecture of a live bot, connecting to a real exchange with ccxt, order and position management, a resilient event loop, and a safe path from paper trading to a VPS deployment.
MQL5 & Expert Advisors
Leave Python behind and build a real Expert Advisor: the MetaTrader terminal, the MQL5 language and its event model, indicator handles, a full moving-average-cross strategy wired to the CTrade order engine, then backtesting, optimising and going live.
Going Live: Production, Monitoring & Psychology
The final mile: the go-live checklist, production monitoring and alerting, kill switches, journaling and reviewing a live edge, and the psychology of leaving an automated system alone — plus where to go next.