Learn Quantitative
Finance
A progressive curriculum that takes you from zero to quant. visual learning, hands-on Python code, real case studies from the V7 engine, and the same techniques behind 59.2% win rate across 4,505 trades.
From Zero to Quant
A structured learning path designed by a practicing quant. Every concept builds on the last.
Beginner
Level 1Foundation concepts — no prior quant knowledge needed
Intermediate
Level 2Statistical methods, Python for finance, feature engineering
Advanced
Level 3Machine learning, model building, backtesting frameworks
Expert
Level 4Production systems, risk management, FTMO compliance
Master
Level 5Research, alpha generation, original strategy development
10 Modules. 85 Lessons. Zero Fluff.
each module builds on the last. start from foundations, end at production live trading. every lesson has code, formulas, quizzes, and assignments.
Foundations
What is quant trading, risk fundamentals, statistical thinking, Python basics, and market microstructure.
Statistics
Hypothesis testing, time series, feature engineering, alpha concepts, and position sizing.
ML Pipeline
The 3-layer ML pipeline, entry gates, exit management, supervised learning, and tree models.
Deep Learning
Neural networks, LSTMs, ensembles, model selection, and feature importance — applied to markets.
Risk Management
VaR, Expected Shortfall, Monte Carlo, drawdown protection, stress testing, and regulatory frameworks.
Validation
Walk-forward, PBO, backtesting, sensitivity analysis, documentation, and regulatory compliance.
Alpha & Signals
Information coefficient, signal decay, alt data, factor models, regime detection, and alpha research.
StatArb
Pairs trading, cointegration, Kalman filters, spread modeling, and portfolio neutrality.
Derivatives
Black-Scholes, volatility surfaces, Monte Carlo pricing, Greeks, exotics, and stochastic calculus.
Production
Data pipelines, APIs, model deployment, containerization, monitoring, FTMO compliance, and portfolio construction.
Which Quant Are You?
Answer 7 quick questions and we'll match you to the career track that fits your personality, interests, and strengths.
Takes about 2 minutes • No sign-up required
Explore by Career Track
same lessons, different lenses. each track curates a learning path for a specific quant career. take the assessment quiz above to find your best match.
Quantitative Researcher
Discover and validate tradable alpha signals using rigorous statistical methods and machine learning.
Quantitative Trader
Execute systematic trading strategies across asset classes with ML-driven decision making.
Quantitative Developer
Build high-performance trading infrastructure, data pipelines, and ML model deployment systems.
Alpha Researcher
Specialize in discovering novel alpha signals — the raw material of profitable trading strategies.
Statistical Arbitrage Quant
Exploit relative mispricings between related instruments using cointegration and mean-reversion models.
Risk Quantitative Analyst
Model, measure, and manage financial risk using VaR, CVaR, stress testing, and Monte Carlo methods.
Pricing / Derivatives Quant
Develop mathematical models for derivatives pricing, volatility surfaces, and exotic instruments.
Model Validation Quant
Independently validate quantitative models to ensure accuracy, robustness, and regulatory compliance.
Quantitative Data Scientist
Apply machine learning and big data techniques to financial datasets for prediction and insight generation.
How We Teach
ELI5 First, Math Second
Every concept starts with a simple analogy you'd explain to a friend. Then we layer in the math. You understand the "why" before the "how."
Real Code, Not Pseudocode
Every lesson includes runnable Python code. Not toy examples — actual implementations using the same libraries quant funds use: XGBoost, pandas, numpy, PyTorch.
Visual Learning
Complex concepts are shown, not just told. Interactive charts, 3D surfaces, animated diagrams — because your brain processes visuals 60,000x faster than text.
Test Your Understanding
Each lesson ends with a quiz and a hands-on assignment. no moving forward until you truly get it. this is how real quant skills are built — through practice, not passive reading.
Ready to think like a quant?
The same framework behind 59.2% win rate, +533.9R, and 0.08% breach probability — broken down into digestible lessons anyone can follow.
Start Lesson 1 →