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Mathematics for AI in Real-world Systems

MATH4120

Mathematical Modelling and Programming

BSc MARS — 2026–27

Welcome. Here you will find everything for MATH4120: lecture notes to read, computation lectures to watch and run, and computer labs to work through. No software to install — all interactive notebooks run directly in your browser.

Full Lecture Notes (PDF)

Week 1 What is a mathematical model?
The modelling cycle; units and dimensions; a first ODE from a rate law.
Week 2 Dimensional analysis and nondimensionalisation
Characteristic scales; nondimensionalising an ODE; solution collapse.
Week 3 The Buckingham Π theorem
Dimension matrices; finding Π-groups systematically; physical similarity.
Week 4 First-order ODEs: rate laws and separable equations
Deriving ODEs from rate laws; separable solutions; exponential growth and decay.
Week 5 Logistic growth: equilibria and stability
The logistic equation; finding and classifying equilibria; phase-line analysis.
Week 6 Linear first-order ODEs and the integrating factor
Forcing and relaxation; the integrating factor method; fitting parameters to data.
Week 7 Harvesting, thresholds, and bifurcation
Harvesting models; tipping points; bifurcation diagrams; catastrophe.
Week 8 Two-species systems and phase planes
Coupled ODEs; nullclines; phase portraits; the Lotka–Volterra predator–prey model.
Week 9 Second-order ODEs and simple harmonic motion
Constant-coefficient ODEs; spring–mass–damper; overdamping, critical damping, oscillation.
Week 10 Numerical ODE solving: Euler, RK2, and error
Implementing Euler and RK2 from scratch; global error; stability; comparison with solve_ivp.
Week 11 Self-similarity and scaling capstone
Scaling collapse revisited; dimensional analysis in action; project and report clinic.