University calculus and multivariable methods
Practise improper integrals, series, gradients and multiple integrals, with explicit conditions and worked examples.
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Short courses with clear notes, worked examples, quizzes that mark themselves and printable study guides. Start any lesson, no account needed.
34 courses available
Practise improper integrals, series, gradients and multiple integrals, with explicit conditions and worked examples.
Develop matrix, vector-space and projection reasoning before using least squares.
Connect initial conditions, linear differential equations and numerical approximation with error and conditioning.
Work with conditional probability, normalization, densities and expectation.
Build epsilon proofs and distinguish pointwise convergence, uniform convergence and compactness.
Study groups, vector-space quotients and proof techniques with carefully scoped definitions.
Study complex analysis, residues, Fourier series, PDE boundary conditions and convexity through focused lessons.
Connect rotation, oscillations, central forces and continuous wave models.
Work with Gauss laws, electrical field models, thermodynamic laws and electromagnetic waves.
Compare relativistic measurement with quantum states, the Schrödinger equation and uncertainty.
Use Lagrangian and Hamiltonian methods, then interpret canonical ensembles.
Explore perturbation theory, scattering, variational quantum estimates and a conceptual bridge to general relativity.
Learn sky motion, the Solar System, astronomical light and safe telescope interpretation.
Connect parallax, magnitudes and stellar structure to evolutionary paths and remnants.
Explore two-body motion, spacecraft data, planet detection and atmospheric interpretation.
Study galaxy models, cosmic expansion, black holes and uncertainty in astronomical measurements.
Understand learning tasks, datasets, honest evaluation, privacy and human responsibility. No paid AI tool is required.
Work through regression, gradients, classification and generalization using paper-based examples.
Compare trees, clustering, PCA and validation without confusing training performance with evidence of generalization.
Build from artificial neurons and backpropagation to attention and embedding geometry.
Practise clear prompting, retrieval-grounded workflows, evidence checking and permission-aware deployment.
Learn core Python concepts with paper-based reasoning and small code-reading tasks.
Study HTML, CSS, JavaScript and accessible web structure without a paid bootcamp.
Learn tables, queries, joins and data modelling with original exercises.
Work through data cleaning, visualization, modelling and interpretation.
Study defensive security, privacy and risk management without offensive exploitation instructions.
Learn descriptive statistics, probability, sampling and inference with worked reasoning.
Learn statements, double entry and basic analysis with fictional examples.
Learn formulas, references, cleaning and charts for practical study and office work.
Learn scope, scheduling, risk and communication through practical scenarios.
Learn research questions, source evaluation, argument structure and citation practice.
Learn audiences, funnels, content, measurement and responsible experimentation.
Learn hierarchy, typography, layout and accessible visual communication.
Build retrieval, note-making, planning and evidence-checking skills for independent learners.
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