Scientific Computing with NumPy – Python Data Science

Scientific Computing with NumPy – Python Data Science 

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We’re a couple (Eirik and Stine) who love to create high-quality courses! In the past, Eirik has taught both Python and NumPy at the university level, while Stine has written learning material for a university course that has used NumPy. We both love NumPy and can’t wait to teach you all about it!

What this course is all about:

In this course, we will teach you the ins and outs of the Python library NumPy. This library is incredibly powerful and is used for scientific computing, linear algebra, image processing, machine learning, and much more. If you are interested in one of these topics, or simply want to get started with data science in Python, then this is the course for you!

Topics we will cover:

We will cover a lot of different topics in this course. In order of appearance, they are:

Introduction to NumPy

Working with Vectors

Universal Functions and Plotting

Randomness and Statistics

Making and Modifying Matrices

Broadcasting and Advanced Indexing

Basic Linear Algebra

Understanding n-dimensional Arrays

Fourier Transforms

Advanced Linear Algebra

Saving and Loading Data

By completing our course, you will be comfortable with NumPy and have a solid foundation for learning data science in Python.

Don’t forget to check out the exercises in this course. Link in the class project.

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