FREE ADVANCED COURSE
Complete trading course: market structure, ICT, SMC and algorithmic trading
A free 23-lesson course: from market structure to liquidity, order blocks and fair value gaps, from a trading model to backtesting, all the way to algorithmic trading in Python. With exercises and a critical lesson on the real evidence behind ICT and SMC.
23 lessons · 5 modules · 3 hours of reading, approx. · updated 2026-09-19
How to use this course
Every lesson ends with a practical exercise: do it before moving to the next. Educational content, not financial advice. ICT and SMC concepts are presented as hypotheses to verify, not guaranteed methods: module 4 teaches you to measure whether they really work.
Module 1 — Market structure
The foundations: how to read a chart objectively, with no indicators, before talking about ICT or SMC.
- 1Market structure: swings, highs and lowsWhat swing highs and swing lows are, and how to read a trend by looking at price alone. · 8 min
- 2Break of Structure and Change of CharacterWhen structure continues (BOS) and when it changes (CHoCH or MSS): operational definitions without ambiguity. · 9 min
- 3Multi-timeframe analysis: top-downHow to use different timeframes for direction, area and entry without getting confused. · 8 min
- 4Trend, range and market phasesRecognising which phase you are in completely changes which kind of setup makes sense. · 7 min
Module 2 — SMC and ICT concepts
Liquidity, order blocks, fair value gaps, premium and discount: operational definitions, how to spot them and where they fail.
- 5Liquidity: buy-side, sell-side and sweepsWhy price tends to reach the levels where stops accumulate, and how to recognise a sweep. · 9 min
- 6Order block: definition, use and limitsWhat an order block is, how to identify it without too much subjectivity, and why it is not a guaranteed bounce. · 9 min
- 7Fair Value Gap (imbalance)How a fair value gap forms, how to measure it and how to handle it in a trading plan. · 8 min
- 8Premium, discount and equilibriumSplitting the range in half to see whether price is expensive or cheap, and the concept of optimal trade entry. · 7 min
- 9Breaker block and mitigation blockOrder block variants: what they are, when they appear and how not to overcomplicate things. · 6 min
Module 3 — Timing and trading models
Sessions, killzones, daily bias and a complete entry model with stop, target and a written plan.
- 10Sessions and killzones: when to tradeThe time windows in which the ICT approach looks for setups, and how to translate them to your time zone. · 7 min
- 11Power of 3: accumulation, manipulation, distributionThe conceptual model that describes a typical day in three phases, and how to use it without forcing it. · 7 min
- 12How to build the daily biasA simple, repeatable method to decide whether to look for buys or sells before the open. · 8 min
- 13Trading model: sweep, MSS and FVG entryA complete setup step by step, from conditions to exit plan, to be tested before use. · 11 min
- 14Trade management: stops, targets and partial exitsHow to size, how to protect and when to exit, with rules decided before entering. · 8 min
- 15Trading plan and pre-trade checklistTurning everything into an operating document and a ten-second checklist to use before every entry. · 7 min
Module 4 — Validating what you learn
Backtesting, statistics and an honest lesson on the evidence for (and against) ICT and SMC. This is the module that separates people who learn from people who fool themselves.
- 16Manual backtesting without fooling yourselfHow to test a setup by hand on historical charts while avoiding the biases that make any method look like a winner. · 9 min
- 17The statistics that matter: R, expectancy and drawdownHow to read a system's results: R multiples, expectancy, profit factor, drawdown and sample uncertainty. · 10 min
- 18What we really know about ICT and SMC: evidence and limitsA critical lesson: what is plausible, what is unproven, and how to use these concepts with a scientific attitude. · 8 min
Module 5 — Algorithmic trading
From written rules to Python code, backtesting and execution: how to automate (and verify) an approach without illusions.
- 19Introduction to algorithmic tradingWhat it is, which kinds of strategies exist, advantages, limits and tools to get started. · 8 min
- 20From idea to rules: writing a testable strategyHow to turn a discretionary concept into numeric rules, without ambiguity and with few parameters. · 9 min
- 21Coding swings and fair value gaps in PythonTwo clean pandas functions to detect swings and FVGs, with attention to look-ahead. · 12 min
- 22Backtesting without illusions: costs, overfitting and walk-forwardA minimal Python backtest with costs, the statistics in R and the techniques for not fooling yourself. · 12 min
- 23Execution, monitoring and risk of an algorithmFrom test to live account: paper trading, infrastructure, safety limits and what to check every day. · 9 min