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Module 1 · Vectors, Spaces & Linear Maps
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Module 2 · Gaussian Elimination & Determinants
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Module 3 · Eigenvalues & Diagonalization
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Module 4 · Orthogonality
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Module 5 · Symmetric Matrices & SVD
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Module 6 · Probability Foundations
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Module 7 · Random Variables & Distributions
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Module 8 · Expectation & Variance
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Module 9 · Approximations & the CLT
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Module 10 · Joint Distributions & Covariance
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Physics 1 · Classical Mechanics
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Vectors
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Vector Spaces & Subspaces
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Linear Maps
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Matrices
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Systems & Gaussian Elimination
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Determinants
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Eigenvalues & Diagonalization
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Applications
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Inner Products & Orthonormal Bases
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Projections & Least Squares
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Gram-Schmidt & Orthogonal Maps
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Symmetric Matrices & the Spectral Theorem
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Singular Value Decomposition
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Probability Spaces & Rules
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Conditional Probability & Independence
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Random Variables & Distributions
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Common Distributions
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Expectation & Variance
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More Distributions
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Normal approximation & the CLT
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Estimation & the Law of Large Numbers
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Joint distributions
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Multivariate expectation & variance
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Covariance & correlation
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Kinematics
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Newton's laws
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Work & energy
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Momentum
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