NumPy Course: The Hands-on Introduction To NumPy (2024)

NumPy is written specifically for working with large quantities of numbers. It can be used by itself, but it’s also at the core of the most popular data science and machine learning packages, like Pandas and TensorFlow.

NumPy has a strong focus on performance. For this reason, NumPy is written mainly in a low-level programming language called C. It offers easy-to-use bindings for us Python users, so we don’t have to worry about low-level stuff.

In this course, you will learn NumPy from the ground up. We cover all the essential concepts and work up to some pretty advanced topics.

You won’t regret learning NumPy using this course if you are serious about:

• Scientific computing
• AI and machine learning
• data science and data analysis

It offers a great starting point and lays a solid foundation to build on.

Earn a certificate of completion

To use on your CV and LinkedIn

Easy to use PDF format

Easy navigation

A distraction-free course system designed for optimal learning

Keep track of progress

Mark lessons as complete and continue where you left off

Learn at your own pace​

I get it; we’re all busy! This course allows you to learn at your own pace. No pressure!

Use quizzes to make sure you mastered the material

With helpful feedback

Lifetime access & Easy refunds

You get lifetime access to the course, including all its updates and improvements (for as long as this site exists).

And just in case you discover it’s not for you: no problem! Let us know within five days of your initial purchase, and we’ll happily refund your money through the same payment method you used to buy the course.

Up-to-date

Python Land constantly monitors and tests new Python releases and updates the courses accordingly. You can rest assured that this course will work with the latest Python version.

About the authors

This course was written by Diego Barba and edited and proofread by Erik van Baaren.

About Diego

Diego Barba is a computational physicist turned quantitative finance researcher and the main writer of this NumPy course.

His principal areas of interest:

• scientific computing
• financial machine learning
• concurrency
• distributed systems

Diego’s favorite programming languages are Python and Rust. He also writes on Medium.

About Erik

Python Land is owned and operated by Erik van Baaren (more about him here), who also happens to be the author of numerous articles, tutorials, and courses. Erik continually tweaks and updates the courses to reflect the latest developments, so you can be sure this course is up-to-date.

With 25 years of experience as a professional software developer, Erik holds a Master of Science degree in computer science.

Frequently Asked Questions

Can I get help if I get stuck?

Erik is available for questions and comments through the contact form (e-mail). If you get stuck, he will do everything possible to get you going again. This personal approach is also what sets this course aside from others. Erik values all input and encourages you to get in touch if needed. Your input will no doubt help to improve the course.

Will the NumPy course stay the same after my purchase?

We continuously update the Python courses to reflect the latest developments in Python. We promptly fix mistakes and issues brought to our attention. You will keep your lifetime access to this course and all its improvements.

Is there a refund policy?

Yes. If you don’t like the course, we’ll refund your money if you ask within five days of your initial purchase. Refunds are limited to one refund per person per course.

Which OS do I need for this course?

You can follow the course on Windows, MacOS, and Linux.

Can I follow this course on a mobile phone or tablet?

Yes. The course system will work fine on mobile phones or tablets and adapt to smaller screens. However, some of the code examples might be harder to read. Also, you need a PC with a Python installation to get the actual practice. So yes, you can read the theory and do quizzes on a mobile phone, but I strongly recommend a PC for the best experience.

What experience level is required to follow this course?

You’ll need basic programming knowledge and basic proficiency in Python. If you are unsure, you can follow our Python Fundamentals courses. In addition to Python, this course is all about numbers and NumPy, so any math knowledge you have will help you grasp the topics quicker.

How long will it take to finish the NumPy course?

It depends on your experience level, the effort you put into the exercises, extra material/links, etc. As a very rough guideline, you will spend about 40 hours before finishing the course.

Can I try it before I buy it?

Yes, you can! See below. There are several sample lessons open for everyone to see and try. In addition, there’s a refund policy that should give you some piece of mind.