Foundational Mathematical Training
Build the mathematical base needed for AI, quantum computing, cryptography, data science, research, and advanced technical work. QF foundational programmes help learners move from scattered techniques toward the structures, proofs, and methods used in serious technical fields.
Foundational Programmes
These programmes cover the core mathematical language used across QF study routes. Onboarding helps decide which topics should come first, and which can wait until a later stage.
Advanced Linear Algebra for ML
Vector spaces, linear maps, eigenspaces, spectral methods, and the linear algebra used in machine learning.
Measure Theory & Functional Analysis (Module I)
Measure, integration, Hilbert spaces, and functional analysis for probability, quantum mechanics, and advanced analysis.
A Crash Course on ODEs
Ordinary differential equations, phase portraits, stability, and the modelling language used in physics, engineering, and applied mathematics.
Group Theory, Topology & Manifolds
Groups, topological spaces, manifolds, and the geometric language used in modern mathematics, quantum theory, and parts of AI.
Mathematical Foundations for Quantum Computing
Linear algebra, probability, group theory, tensor products, and Hilbert space methods for quantum computation.
Real Analysis (Module I)
Sequences, limits, continuity, differentiation, and integration, taught with the proof discipline needed for advanced mathematics.
Real Analysis (Module II)
Metric spaces, convergence, compactness, and more advanced analysis, with links to machine learning theory and research.