Linear Algebra for Data Science in Python

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Get started with using linear algebra in your data science projects.

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19 on-demand videos & exercises
Level: All Levels
56 mins
Access on mobile, web and TV

What to know about this course

Vectorizing your code is an essential skill to make your calculations faster and take advantage of the capabilities of modern machine and deep learning packages. This course will get you up and running with linear algebra fundamentals for data science in Python.

In this course, you will learn about scalars, vectors, and matrices and the geometrical meaning of these objects. You will also learn how you should use linear algebra in your Python code. In addition to this, you’ll be able to perform operations such as addition, subtraction and dot product. As you cover further sections, you’ll focus on the different syntactical errors you can encounter while vectorizing your code.

By the end of this course, you will have gained the skills you need to use linear algebra confidently in your data science projects. All code and supporting files for this course are available at -

Who's this course for?

This course is designed for aspiring data scientists or anyone who wants to learn linear algebra in Python.

What you'll learn

  • Focus on the addition and subtraction of Matrix.
  • Understand errors when adding matrices.
  • Learn why linear algebra is useful.
  • Key Features

    • Learn linear algebra for data science and understand the essential concepts.
    • Understand matrix, scalars, and vectors and learn how to use them.

    Course Curriculum

    About the Author

    Data Circuit

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