Linear Algebra for Data Science & Machine Learning A-Z 2023

Linear Algebra for Data Science, Big Data, Machine Learning, Engineering & Computer Science. Master Linear Algebra

Created by Kashif A. Abdullah A. | 18 hours on-demand video course

DO YOU WANT TO LEARN LINEAR ALGEBRA IN AN EASY WAY? Great! With 22+ hours of content and 200+ video lessons, this course covers everything in Linear Algebra, from start till the end! Every concept is explained in simple language, and Quizzes and Assignments (with solutions!) help you test your concepts as you proceed. Whether you’re a student, or a professional or a Math enthusiast, this course walks you through the core concepts of Linear Algebra in an easy and fun way!

What you’ll learn

Fundamentals of Linear Algebra and how to ace your Linear Algebra exam
Basics of matrices (notation, dimensions, types, addressing the entries etc.)
Operations on a single matrix, e.g. scalar multiplication, transpose, determinant & adjoint
Operations on two matrices, including addition, subtraction and multiplication of matrices
Performing elementary row operations and finding Echelon Forms (REF & RREF)
Inverses, including invertible and singular matrices, and the Cofactor method
Solving systems of linear equations using matrices and inverse matrices, including Cramer’s rule to solve AX = B
Properties of determinants, and how to perform Gauss-Jordan elimination
Matrices as vectors, including vector addition and subtraction, Head-to-Tail rule, components, magnitude and midpoint of a vector
Vector spaces, including dimensions, Euclidean spaces, closure properties and axioms
Linear combinations and span, spanning set for a vector space and linear dependence
Subspace and Null-space of a matrix, matrix-vector products
Basis and standard basis, and checking if a set of given vectors forms the basis for a vector space
Eigenvalues and Eigenvectors, including how to find Eigenvalues and the corresponding Eigenvectors
Basic algebra concepts ( as a BONUS)
And so much more…..