All the material shared in this section is not mine and is shared by the mentioned authors in their webpages. The only objective of this page is to provide useful and free-access material for a complete and deep understanding of Math. I'm probably not aware of many good lecture notes/courses, so feel free to send me additional references to add!
Online course held by W. Gilbert Strang (MIT) for advanced undergraduates and graduate students
A more advanced course by Terence Tao
3blue1brown animated short lectures that give a deep understanding of the essentials of Linear Algebra (and many other topics)
Online course held by Claudio Landim (IMPA) for advanced undergraduates and graduate students
Books by Efe A. Ok (NYU), with more advanced material on Measure Theory. At the same link you can find also material for applied point-set topology and order theory
Lecture Notes by Gabriel Khan (ISU) based on Royden-Fitzpatrick's textbook and the lecture notes by Timothy McNichol
Book "Introduction to Real Analysis, Volume I" and "Volume II" by Jiří Lebl
More advanced courses on Analysis I and Analysis II and Measure Theory by Terence Tao
Asymptotic Theory notes, more oriented to statistic by David R. Hunter (UPenn)
Piotr Zwiernik's Lecture notes, which cover an introductory course in Real Analysis, Linear Algebra, Measure Theory, Fixed Point theorems and Correspondences
Various Courses from the department of Mathematics (Oxford)
Course on Differential Equations and Linear Algebra by Gilbert Strang (MIT)
Youtube course by Rajiv Sethi
Elements of information Theory by Thomas M. Cover and Joy A. Thomas
Convex Optimization by S. Boyd and L. Vandenberghe
The Elements of statistical learning by T. Hastie, R. Tibshirani and J. Friedman
Foundations of Machine Learning by M. Mohri, A. Rostamizadeh and A. Talwalkar