Courses from 1000+ universities
Coursera’s flagship credentials may carry big brand names, but who’s actually creating the content?
600 Free Google Certifications
Management & Leadership
Entrepreneurship
Digital Marketing
Understanding Clinical Research: Behind the Statistics
EU policy and implementation: making Europe work!
.ANIMATIONs
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Learn Vector Spaces, earn certificates with free online courses from MIT, IIT Madras, IIT Kharagpur, Rice University and other top universities around the world. Read reviews to decide if a class is right for you.
This course is all about matrices, and concisely covers the linear algebra that an engineer should know. We define matrices and how to add and multiply them, and introduce some special types of matrices.
Explore lattice topological phases with Fiona Burnell, covering lattice Hamiltonians, vector spaces, local rules, and gauge choices in this comprehensive lecture on advanced quantum physics concepts.
Explore the dimension formula for vector spaces through worked examples and a complete proof. Learn to calculate dimensions of subspaces and their intersections in R^4.
Explore vector space axioms with concrete examples, including addition and scalar multiplication maps, 8 key axioms, and proofs for 3D coordinate vectors. Gain insights into unique properties of vector spaces.
Analyze geometric differences in representations from bilingual vs. multilingual translation models, focusing on isotropy and intrinsic dimensionality to understand performance disparities.
Explore monogenic functions in infinite-dimensional vector spaces, their relation to spatial harmonic functions, and implications for complex analysis beyond traditional Cauchy integral formulas.
Learn the mathematics behind linear algebra and link it to matrix software development.
Un MOOC francophone d'algèbre linéaire accessible à tous, enseigné de manière rigoureuse et ne nécessitant aucun prérequis.
This course is an introduction to linear algebra. You will discover the basic objects of linear algebra – how to compute with them, how they fit together theoretically, and how they can be used to solve real problems.
Learn mathematical methods for data analysis including mathematical formulations and computational methods. Some well-known machine learning algorithms such as k-means are introduced in the examples.
This course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics and social sciences, natural sciences, and engineering.
Master matrix theory and linear algebra, exploring systems of equations, vector spaces, determinants, eigenvalues, and applications in various disciplines. Gain practical skills for solving complex mathematical problems.
Master algebra and MATLAB to solve large systems of differential equations, explore vector spaces, tackle eigenvalue problems, and model real-world phenomena.
Get personalized course recommendations, track subjects and courses with reminders, and more.