Maths for Data Science by DataTrained

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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.

  1. Lessons on Math for Data Science & Machine Learning:

  2. Understand how to work with vectors in Python

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

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

  5. Matrix Multiplication: Understand how to multiply matrices in Python

  6. Matrix Division: Understand how to divide matrices in Python

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

  8. Gaussian Elimination: Understand how to apply Gaussian Elimination

  9. Determinants: Understand how to work with determinants in Python

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

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

  12. Eigenvectors: Recognize how to obtain eigenvectors from eigendecomposition in Python

  13. 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/maths-for-data-science-by-datatrained/