Catalog
Courses
Quantitative finance, built from Ibrahim Lanre Adedimeji's research writing — each lesson rigorous, each formula rendered.
Foundations
5 coursesThe math spine — probability, calculus, analysis, linear algebra.
Mathematical Foundations of Quantitative Finance
The math a working quant actually uses — probability, differential equations, stochastic calculus, the Black–Scholes model, and numerical methods — built from the ground up with full derivations, worked examples, and graded problems.
Calculus for Quants
The calculus a quant uses every day — limits, derivatives, Taylor series, integration, multivariable gradients and Lagrange multipliers, and vector calculus — built with full derivations and worked examples.
Real Analysis for Quants
The rigorous foundation under calculus and probability — completeness, sequences and series, topology and continuity, Riemann and Lebesgue integration, and an introduction to functional analysis (Banach/Hilbert/L^p).
Linear Algebra & Optimization for Quants
The other half of quant math — vectors, matrices, eigenvalues, SVD, PCA, least-squares regression, and convex optimization — built to where you can extract PCA factors and solve a Markowitz portfolio by hand.
Measure-Theoretic Probability
Probability made rigorous — sigma-algebras and measures, random variables as measurable maps, expectation as a Lebesgue integral, conditional expectation as an L^2 projection, and the limit theorems (LLN, CLT, extreme value) that underpin risk.
Advanced
4 coursesResearch-grade pricing — jumps, stochastic vol, microstructure, XVA.
From Diffusion to Jumps: Lévy Models in Finance
Why Brownian motion underprices tail risk, and how Lévy processes fix it.
Stochastic Volatility & Measure Change
The Heston model and the Girsanov change of measure behind modern pricing.
Hawkes Processes & Market Microstructure
Self-exciting events, volatility clustering, and order-book dynamics.
BSDE, XVA & Credit Risk
The frontier of derivatives valuation — backward SDEs and nonlinear Feynman–Kac, counterparty credit risk, the full XVA stack (CVA/DVA/FVA/KVA), and the Monte-Carlo and deep-BSDE methods that price them.
Implementation
1 coursesThe code half — production C++ and high-performance computing.