Maths for Data Science by DataTrained

Explore the application of key mathematical topics related to linear algebra with the Python programming language
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Explore the application of key mathematical topics related to linear algebra with the Python programming language

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

Course content

1 section13 lectures55m total length
  • Introduction
    01:09
  • Understand how to work with vectors in Python
    05:23
  • Understand the Basis and Projection of Vectors in Python
    05:23
  • Work with Matrices
    03:34
  • Matrix Multiplication
    04:33
  • Matrix Division
    04:30
  • Linear Transformations
    03:28
  • Gaussian Elimination
    02:48
  • Determinants
    05:14
  • Orthogonal Matrices
    04:52
  • Eigen values
    05:45
  • Eigenvectors
    04:29
  • PseudoInverse
    04:06

Instructor

Data Scientist and HR Head at DataTrained
Ajay Nadia
  • 4.4 Instructor Rating
  • 281 Reviews
  • 17,120 Students
  • 1 Course

I regard myself as a divine professional and have got 6 years of experience into HR and have got more than 7 years of experience  in HR Analytics. I am heading the HR analytics team at DataTrained and is also heading the HR team.

This course has been designed for the students who want to brush up their basics on math usage in data science using Python as a tool.