Build Your Mathematical Advantage
An outcomes-driven curriculum designed to bridge the gap between abstract mathematics and practical applications across multiple domains. Think of QF Academy as an exclusive training environment designed to help serious professionals build and sustain mathematical fitness at a high level.
Explore Plans →Foundational Core (Self-paced)
Master the essential maths for an advanced career in science and technology.
Advanced Linear Algebra for ML
Bridge the gap between engineering and research with a rigorous treatment of vector spaces and linear maps.
Measure Theory and Functional Analysis (Module I)
Explore the concepts of measure, integration, and Hilbert spaces, which are essential for modern probability theory and quantum mechanics.
A Crash Course on ODEs
Learn to model and solve the differential equations that describe dynamical systems in physics, engineering, and finance.
Group Theory, Topology & Manifolds
Explore the essential mathematical structures for advanced applications in AI, ML, and Quantum Computing.
Mathematical Foundations for QC
Build a rigorous mathematical foundation in linear algebra, probability, and group theory for quantum computing.
Real Analysis (Module I)
Build the rigorous foundation essential for understanding machine learning theory and advanced algorithms.
Real Analysis (Module II)
Continue your journey into advanced analysis, covering topics essential for deep learning theory and modern research.
Focus Tracks (Guided Self-paced)
Intensive, module-based courses aimed at helping you fast track into specific advanced mathematical territories for frontier research in AI, Quantum and other emerging fields. These tracks rotate periodically to cover emerging research areas.
Algebraic Topology: A Gentle Introduction
Unlock the deep connections between algebra and geometry. A critical toolkit for theoretical physics, geometric deep learning, and topological data analysis.
Get StartedMathematics of Topological Data Analysis (TDA): A Gentle Introduction
This track explores the intersection of algebraic topology and computer science, focusing on algorithms to compute topological invariants from discrete data.
Secure your placeModule I
Geometric Foundations and Homotopy
Module II
Homology and Algebraic Machinery
Module III
Cohomology and Persistence
Module IV
Advanced Topics: Sheaves and Discrete Morse Theory
Stochastic Processes (Random Walks): A Rigorous Introduction
This track offers a comprehensive entry point into the world of stochastic processes, focusing specifically on the mathematical theory of Random Walks. While designed as an introduction that assumes minimal prior knowledge of probability theory, this course moves beyond intuition to establish a firm foundation in Measure Theory and rigorous analysis.
Secure your placeModule I
Measure-Theoretic Foundations
Module II
Random Variables & Independence
Module III
Random Walks & Convergence Laws
Module IV
The Central Limit Theorem & Asymptotics
Project-based Specialisations
Apply your knowledge to become a subject matter expert.
Lie Groups with Applications
An advanced course on Lie groups and their applications in physics, geometric deep learning, and quantum computing.
Topological Data Analysis
Discover how to analyze the shape and structure of complex datasets using topological methods for novel insights in data science.
Outcomes-Driven Guarantee
Complete a specialisation, apply skills for 8 weeks. If you don't find an opportunity, we refund you.