Full university physics courses, free to watch.

Courses

• Special Relativity — From two postulates to the geometry of spacetime.
• Waves & Oscillations — One equation behind sound, light, strings and quantum waves.
• Differential Equations — From slope fields to the heat, wave and Laplace equations.
• Probability & Statistics — From the axioms to inference, regression and Bayes.
• Statistical Mechanics — From microstates to the renormalization group.
• Introduction to Quantum Computing — From one qubit to Shor, Grover and error correction.
• Linear Algebra — Elimination, eigenvalues and the SVD — with the geometry kept in view.
• Mathematical Physics — The mathematical toolkit a working physicist actually uses.
• Quantum Field Theory II — Gauge theory, symmetry breaking, and the Standard Model assembled
• Measure and Integration — Why length needs a theory, and what integration becomes once it has one
• Physical Organic Chemistry — A mechanism is a hypothesis, and this is how you test it
• Multimodal Generative AI — Diffusion, flows, and the models that join images to language
• Machine Learning Systems: GPU Computing, AI Compilers and Efficient Inference — Where the FLOPs actually go, from tensor layout to attention kernels
• Introduction to Particle Physics — The particle zoo, and the symmetries that order it
• Introduction to Compilers and Programming Languages — What compilation must preserve, from source text to machine instructions
• Inorganic Chemistry — Symmetry, d electrons and what the rest of the periodic table does
• Introduction to Topology — Nearness without distance, and the invariants that survive stretching
• Introduction to Computer Security — Assets, adversaries and trust boundaries — and the engineering that holds them
• Quantum Chemistry — The equation that cannot be solved, and the approximations chemistry is built on
• Introduction to Nuclear Physics — What holds a nucleus together, and what happens when it lets go
• Environmental & Atmospheric Chemistry — The atmosphere and ocean as reactors, and how we know what they are doing
• Numerical Analysis and Scientific Computing — Algorithms, approximation error and when to trust a computed answer
• Genetics — From Mendel's counts to reading variation across whole genomes
• General Chemistry — From the inside of an atom to why a reaction goes, and how fast
• Computational Chemistry — What a computed number means, and when to disbelieve it
• Cell Biology — What a cell is made of, how it runs, and how it divides
• Human & Animal Physiology — How organ systems keep an animal's internal state in balance
• Bioinformatics — Algorithms and statistics for reading sequences and genomes
• Biophysics — The physics of the cell, one kT at a time
• Neuroscience — From the membrane potential to circuits, memory and neural codes
• Developmental Biology — How a single egg builds a patterned, growing body
• Microbiology & Immunology — Microbes, the immune response to them, and how infections spread
• Ecology — Populations, communities and ecosystems, from growth models to biomes
• Biochemistry — Proteins, enzymes and the metabolic pathways that power the cell
• Evolution — The forces that change populations, and how we reconstruct their history
• Molecular Biology — How DNA is copied, read and regulated, and how we now edit it
• Electrochemistry & Energy Storage — Where a cell's voltage goes, and what that means for batteries and fuel cells
• Spectroscopy & Structure Determination — Reading a molecule's structure from its spectra, and knowing when you are wrong
• Materials & Polymer Chemistry — Why real materials behave nothing like their ideal crystals
• Analytical Chemistry — What a measurement is worth, and how to make one you can defend
• Organic Chemistry — Structure, stereochemistry and the reactions that follow from them
• Physical Chemistry — Statistical mechanics, kinetics and quantum theory as one account of matter
• Introduction to Distributed Systems — Keeping a service correct when messages are lost and machines fail
• Reinforcement Learning — How an agent learns to act from rewards, from bandits to PPO
• Theory of Computation — What machines must remember, what they can decide, and at what cost
• Introduction to Computer Networks — How a message crosses links, routers and protocols to reach its destination
• Operating Systems — How one machine is shared among programs, safely and durably
• Databases & Data Systems — One booking through tables, queries, indexes, transactions and recovery
• Computer Systems — Follow one program from its bits through the processor, memory and OS
• Artificial Intelligence — Search, logic, planning and decisions for explicitly represented problems
• Number Theory — Divisibility, congruences and reciprocity, proved from the ground up
• Nonlinear Dynamics and Chaos — Flows, stability, oscillation and chaos, seen through their trajectories
• Differential Geometry: Curves and Surfaces — How curves and surfaces bend, and what an inhabitant can measure
• Algebra and Functions — Equations, graphs and models, and when an algebraic step is allowed
• Advanced Trigonometry — Triangles, circles and waves, and the identities that connect them
• Geometry — Shape, proof and measurement, built from what each argument can justify
• Intro to Modern Astrophysics — Light, stars, galaxies and the large-scale universe
• Introduction to Condensed Matter Physics — Many-body methods for superconductors, magnets and topological matter
• Fluid Mechanics — How fluids move, from Bernoulli to turbulence
• Introduction to Solid-State Physics — Crystals, phonons, bands and the materials built from them
• Quantum Mechanics II — Symmetry, transitions, scattering, and the road to relativistic quantum theory
• Relativistic Astrophysics & Cosmology — Black holes, compact objects, gravitational waves and the expanding universe
• Quantum Field Theory I — From free fields to Feynman diagrams, loops and renormalisation
• Quantum Mechanics I — Why quantum mechanics is forced on us, and how to calculate with it
• Transformers and Large Language Models — The architecture, the training objective, and the economics of inference
• Optimization — Convexity, gradients, constraints and duality
• Discrete Mathematics — The language of proof, and the mathematics computing is built on
• Building with LLMs — Everything around the model, which is where the engineering actually is
• Deep Learning — Why depth works, and what it takes to train it
• Introduction to Machine Learning — What it means for a machine to learn, and how the classical methods work
• Abstract Algebra — Symmetry, structure, and the objects that formalise them
• Complex Analysis — Why one extra dimension makes analysis rigid, and powerful
• Real Analysis — The proofs behind the calculus you already know
• Multivariable & Vector Calculus — Calculus in more than one dimension, ending in one theorem
• Single-Variable Calculus — Limits, derivatives, integrals and series — built in the right order
• Optics & Photonics — From rays to photons, and the engineering in between
• Algorithms — How to design an algorithm, and how to know it is good
• Introduction to Cosmology — The universe as a physical system with a history
• Analytical Mechanics — Mechanics rebuilt on a variational principle
• Quantum Physics I — Wave mechanics from the Schrödinger equation to the hydrogen atom.
• General Relativity — Foundations — From the equivalence principle to black holes, gravitational waves and cosmology.
• Quantum Physics III — Perturbation theory, the semiclassical limit, scattering and identical particles.
• General Relativity — Tensors and curvature through gravitational radiation, cosmology and black holes.
• Relativistic Quantum Field Theory I — Classical fields to canonical quantisation, path integrals and QED.
• Physics III: Vibrations and Waves — Oscillators, normal modes and the wave equation — through sound, light and dispersion.
• Quantum Physics II — Quantum mechanics rebuilt in Dirac notation — spin, dynamics and angular momentum.
• Atomic and Optical Physics II — Quantum optics, light forces and ultracold Bose and Fermi gases.
• Atomic and Optical Physics I — Resonance, atomic structure, line broadening and coherence.
• Statistical Mechanics II — Landau–Ginzburg theory, the scaling hypothesis and the renormalisation group.
• Statistical Mechanics I — Thermodynamics, kinetic theory and the statistical mechanics of particles.
• The Early Universe — The expanding universe, the microwave background and inflation.
• Introduction to Quantum Mechanics — Quantum mechanics as Cambridge teaches it — from the wavefunction to the hydrogen atom.
• Thermodynamics & Statistical Mechanics — From the zeroth law to the partition function — the four laws, and the microscopic story behind them.
• Electricity & Magnetism — The complete electromagnetism sequence — from Coulomb's law to radiation and relativity.