Maths for Data Science by DataTrained
Requirements
10th class Level math knowledge is expected
Description
Overview: Explore the application of key mathematical topics related to linear algebra with the Python programming language.
Expected Duration: After completion of this course, you should be able to accomplish the objectives from the following lessons and topics.

Lessons on Math for Data Science & Machine Learning:

Understand how to work with vectors in Python

Basis and Projection of Vectors: Understand the Basis and Projection of Vectors in Python

Work with Matrices: Understand how to work with matrices in Python

Matrix Multiplication: Understand how to multiply matrices in Python

Matrix Division: Understand how to divide matrices in Python

Linear Transformations: Understand how to work with linear transformations in Python

Gaussian Elimination: Understand how to apply Gaussian Elimination

Determinants: Understand how to work with determinants in Python

Orthogonal Matrices: Understand how to work with orthogonal matrices in Python

Eigenvalues: Recognize how to obtain eigenvalues from eight decompositions in Python

Eigenvectors: Recognize how to obtain eigenvectors from eigendecomposition in Python

PseudoInverse: Recognize how to obtain pseudoinverse in Python
Who this course is for:
Beginner python developers looking for a data science career
https://www.udemy.com/course/mathsfordatasciencebydatatrained/