The Missing Math & CS classes
addressed to people with little to no math background and who want to specialize in AI/ML.
this list of classes isn't complete yet and may get altered (removing certain courses, adding others), so take it with a grain of salt, it's just a prototype.
courses on ML & AI will be added to the list later on
Course
School
Instructor
Book Recommendation
Keywords
Linear Algebra
MIT
Gilbert Strang
Linear Algebra and Its Applications Book by Gilbert Strang
the 4 fundamental spaces, spectral theorem (decomposition), projection, orthanormal spaces, ...
Discrete Mathematics
NPTEL
Kamala Krithivasan
Naive Set Theory by Paul R.halmos
propositional/predicate logic, set theory, graph theory, combinatorics, automata, ...
Computer science theory :
Course
School
Instructor
Book Recommendation
Keywords
Single Variable Calculus
MIT
David Jerison
calculus eighth edition james stewart
functions, limits, infinitesimal linear approximation (derivation), integration, the fundamental theorems of calculus, basic optimization, ...
Multi Variable Calculus
MIT
Denis Auroux
calculus eighth edition james stewart
parametric equations, partial derivatives, gradients, lagrange multipliers, polar coordinates, vector fields, ...
Advanced Calculus, linear algebra and optimization theory :
Course
School
Instructor
Book Recommendation
Keywords
Linear Programming
Penn State University
Wen Shen
Linear Algebra and Its Applications Book by Gilbert Strang
problem modeling, canonical form, simplex method, convexity, duality, matrix form, primal-dual method, integer programming, ...
Convexity Theory (check lectures on convex sets/functions)
NPTEL
Shirish K. Shevade
NA
Jensen's inequality, convex sets, affine sets, combinations, hulls, polyhedra, hyperplanes ...
Gradient based methods (basic gradient descent + conjugate gradients)
NPTEL
Arghya Deb
linear and non-linear programming third edition david g.luenberger
gradients, optimal direction, optimal step size, ...
more on non-linear programming
NA
NA
linear and non-linear programming third edition david g.luenberger
KKT, constraint programming, barrier methods, convergence, ...
Meta-heuristics
NA
NA
handbook of metaheuristics third edition michle gendreau
modeling, population/instance based methods, tabu search, swarm intelligence, GVNS, genetic algorithms, ...
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
MIT
Gilbert Strang
linear algebra and learning from data by gilbert strang
matrix decomposition, linear regression, neural nets ...
More on Discrete Mathematics :
Course
School
Instructor
Book Recommendation
Keywords
Topological Spaces and Manifolds
NA
NA
NA
NA
Probability Theory & Statistics :
Course
School
Instructor
Book Recommendation
Keywords
Probability Theory (medium)
MIT
John Tsitsiklis
NA
discrete/continuous random variables, PDF, CDF, marginal, joint, conditional probability, random processes, LLN, CLT...
Probability Theory (hard)
HARVARD
Joe Blitzstein
NA
law of total probability, LOTUS, MGF, LLN, CLT, stochastic processes, ...
Information Theory
NA
NA
NA
measure of information, shannon's measure, conditional entropy, mutual information, ...
Statistical Inference (kinda deep)
MIT
Philippe Rigollet
NA
statistical modeling, MLE, MM, LSE, PCA, GLM, hypothesis testing, ...
Statistical Inference (deep)
NPTEL
Somesh Kumar
NA
UMVUE estimators, sufficient statistics, distribution families, neyman-pearson's theorem, likelihood ratio, ...
Time Series
NA
NA
NA
ARIMA, signal decomposition, stationary signals, seasonality, ...
Course
School
Instructor
Book Recommendation
Keywords
Hilbert Spaces (introductory article)
NA
JOEL KLIPFEL
NA
dot-product spaces, infinite vector spaces, ...
Fourier series/trans (from 33 to 37)
Caltech
Ali Hajimiri
NA
orthogonal functions' space basis, duality (spatial/temporal vs frequency domains), ...
Discrete Time Signal Processing
NPTEL
Mrityunjoy Chakraborty
NA
eigen functions, LSI systems, DTFT, ...
Statistical Signal Processing
NPTEL
Prabin Kumar Bora
NA
random processes, wiener filters, ...
Digital Signal Processing
Rensselaer Polytechnic Institute
Rich Radke
NA
Digital Image Processing
Rensselaer Polytechnic Institute
Rich Radke
NA
transformations, spatial fitlers, frequency filters, smoothing, sharpening, edge detection, segmentation, ...