Intermediate Most Popular

Technical Analysis

A rigorous 10-module program that teaches you to read price like a desk analyst — candlestick structure, volume profile, moving averages, momentum oscillators and multi-timeframe confirmation, all tied into a single repeatable decision framework.

32 hours
10 modules
Lifetime access
Certificate
Technical analysis course cover with candlestick chart and moving averages

What you'll learn

  • Read candlestick structure without indicators
  • Use volume profile to define support / resistance
  • Apply moving averages as regime filters
  • Identify momentum exhaustion with oscillators
  • Construct a multi-timeframe thesis
  • Backtest patterns with statistical rigor
  • Journal and review setups systematically
  • Design a personal rule-based playbook

Course modules

MODULE 01

Why technical analysis works (and where it doesn't)

Market microstructure, the role of liquidity and the statistical case for pattern recognition.

MODULE 02

Candlestick structure

Single-bar signals, two-bar patterns, and the difference between signal and noise.

MODULE 03

Trend, range and transition

Classifying market state before applying any strategy.

MODULE 04

Volume profile

Point of control, value area, high- and low-volume nodes as high-probability reference levels.

MODULE 05

Moving averages as regime filters

Simple vs. exponential, 20/50/200 alignment, and avoiding the moving-average fallacy.

MODULE 06

Momentum oscillators

RSI, MACD, stochastics — what they actually measure and the conditions under which they matter.

MODULE 07

Support, resistance and pivots

Objective methods for mapping structural levels without curve fitting.

MODULE 08

Multi-timeframe analysis

Top-down framework: monthly context → weekly bias → daily trigger → intraday execution.

MODULE 09

Backtesting and journaling

Building a repeatable measurement loop so the edge — or its absence — becomes visible.

MODULE 10

Capstone: your personal playbook

Graduation project: compile 3-5 rule-based setups with statistical expectancy and risk-defined sizing.