Focus Tracks
Focus tracks connect foundational mathematics to a defined technical direction. Learners normally take one track at a time, after QF checks their prerequisites and confirms the route fits their current level.
Focus Track Catalogue
Each focus track gives a route through a defined area of advanced mathematics. QF checks prerequisites before the learner starts, so the track is entered at the right level rather than treated as open access to every route.
Algebraic Topology: A Gentle Introduction
Use algebra to study shape. The track covers homotopy, covering spaces, homology, and applications in physics, geometric deep learning, and topological data analysis.
Homotopy and Covering Spaces
Fundamental groups, covering space theory, and applications to topological invariants.
Introduction to Homology Theory
Singular homology, exact sequences, and chain complexes for topological spaces.
Simplicial Homology & Homological Algebra
Computational homology via simplicial complexes and the algebraic machinery behind it.
Modern Applications (AI / Physics)
Geometric deep learning, topological data analysis, and applications in theoretical physics.
Mathematics of Topological Data Analysis (TDA)
Study how topological invariants can be extracted from data through simplicial complexes, homology, persistence, and computation.
Geometric Foundations and Homotopy
Topological spaces, simplicial complexes, and the geometric underpinnings of data analysis.
Homology and Algebraic Machinery
Betti numbers, chain complexes, and the algebraic tools for computing topological features.
Cohomology and Persistence
Persistent homology, barcodes, persistence diagrams, and their stability theorems.
Advanced Topics: Sheaves & Discrete Morse Theory
Sheaf theory, discrete Morse functions, and their applications in data science.
Stochastic Processes (Random Walks): A Rigorous Introduction
A rigorous entry point into stochastic processes through random walks, convergence laws, and measure-theoretic probability.
Measure-Theoretic Foundations
Sigma-algebras, probability spaces, and the measure-theoretic framework for rigorous probability.
Random Variables & Independence
Measurable functions, independence, expectation, and characteristic functions.
Random Walks & Convergence Laws
Simple random walks, recurrence, transience, and the laws of large numbers.
The Central Limit Theorem & Asymptotics
Weak convergence, CLT proofs via characteristic functions, and asymptotic analysis.