Become a quant
through a structured curriculum.
Self-paced lessons from probability and stochastic calculus through options, fixed income, and portfolio management—with computer networking and volatility modeling on the way.
Explore curriculumHow it works
Learn the live curriculum, practise inside lessons, then build projects when they launch.
Step 1
Learn
University-grade lessons across the quant-finance path—from probability to portfolio management.
What's Included
- Introduction to Probability
- Stochastic Calculus
- Options Pricing
- Fixed Income and Interest Rate Models
- Portfolio Management
- Computer Networking (coming)
- Volatility Modeling (coming)
Step 2
Practise
Worked examples and derivations inside lessons turn theory into something you can compute.
What's Included
- Worked examples
- Step-by-step derivations
- Numerical illustrations
- Applied calculations
- Problem sets
Step 3
Projects
In progressHands-on builds are on the way—apply the curriculum in code once projects ship.
What's Included
- Apply units in code
- Build portfolio pieces from lessons
- Projects Lab coming later
Table of Contents
Five live units from probability through portfolio management, plus computer networking and volatility modeling coming next.
1. Introduction to Probability
- • Probability Foundations.5
- • Discrete Random Variables.6
- • Continuous Random Variables.7
- • Further Topics on Random Variables.9
- • Limit Theorems.5
- • The Bernoulli and Poisson Processes.3
- • Markov Chains.5
- • Classical Statistical Inference.5
2. Stochastic Calculus
- • Discrete Martingales and the Gambling Blueprint.5
- • Brownian Motion: Construction and Properties.8
- • Stochastic Integration and Itô's Formula.10
- • Diffusions, SDEs, and the Feynman-Kac Formula.6
- • Change of Measure, Girsanov, and Risk-Neutral Pricing.8
- • Lévy Processes and Jump Calculus.6
3. Options Pricing
- • Foundations of Computational Option Pricing.11
- • Binomial Trees, Barrier and American Options.6
- • Monte Carlo Methods and Stochastic Volatility.9
4. Fixed Income and Interest Rate Models
- • Bond Mathematics and Pricing Fundamentals.
- • Duration, Convexity, and Interest Rate Risk.
- • The Term Structure of Interest Rates.
- • No-Arbitrage Pricing and the Risk-Neutral Framework.
- • Short-Rate Models.
- • Multi-Factor Term Structure Models.
- • The Heath-Jarrow-Morton Framework.
- • The LIBOR Market Model.
- • Interest Rate Derivatives and the Volatility Surface.
- • Swaps, Futures, and Linear Rate Derivatives.
- • Mortgage-Backed Securities and Securitization.
5. Portfolio Management
- • Portfolio Optimisation and Quant Portfolio Construction.11
- • Risk Analytics, Fund Management and Model Risk.8
- • Index Models and Portfolio Computation.3
- • CAPM and Equilibrium Models.7
- • Market Efficiency, Behavioral Finance, and Equity Valuation.6
- • Portfolio Performance Evaluation.5
- • Practitioner Equity Portfolio Management.7
6. Computer NetworkingIn progress
- • Network fundamentals.
- • Protocols and the stack.
- • Latency, throughput, and reliability.
7. Volatility ModelingIn progress
- • Volatility surfaces.
- • Local and stochastic volatility.
- • Calibration and dynamics.
Start with Probability.
Build toward portfolio mastery.
Self-paced units with worked examples—from probability through stochastic calculus, options, fixed income, and portfolio management.