Linear Algebra for Data Science & Machine Learning A-Z 2024
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- At udemy.com you can purchase Linear Algebra for Data Science & Machine Learning A-Z 2024 for only $109.99
- The lowest price of Linear Algebra for Data Science & Machine Learning A-Z 2024 was obtained on December 14, 2024 7:43 pm.
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Linear Algebra for Data Science & Machine Learning A-Z 2024
$109.99 Original price was: $109.99.$12.00Current price is: $12.00.
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Linear Algebra for Data Science & Machine Learning A-Z 2024
★★★★★
$109.99
in stock
Udemy.com
as of December 14, 2024 7:43 pm
Linear Algebra for Data Science, Big Data, Machine Learning, Engineering & Computer Science. Master Linear Algebra
Created by:
Kashif A.
Bestselling Instructor
Bestselling Instructor
Created by:
Abdullah A.
Bestseller Teacher
Bestseller Teacher
Rating:4.66 (773reviews)
4891students enrolled
What Will I 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…..
Requirements
- A passion to learn about Matrices and Vectors
- Ability to perform basic Mathematical operations (+, -, x, ÷) on numbers and fractions
- Knowledge of how to solve a linear equation (e.g. find x in 3x-4=11)
- Understanding of basic Algebra concepts, e.g. Powers and Roots, simplifying Fractions, Factorization, solving Equations and drawing Graphs.
- You only need to know basic Math and Algebra to take this course.
- And the best thing is, most of the above prerequisite topics are covered inside the course 🙂
Target audience
- Students enrolled or planning to enroll in Linear Algebra class, and who want to excel in it
- Professionals who need a refresher in Math, especially Algebra and Linear Algebra
- Engineers, Scientists and Mathematicians who want to work with Linear Systems and Vector Spaces
- Anyone who wants to master Linear Algebra for Data Science, Data Analysis, Artificial Intelligence, Machine Learning, Deep Learning, Computer Graphics, Programming etc.
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