Skip to main content

Learn NumPy with online courses and programs

NumPy is a library for Python that allows users to build multidimensional arrays and high-level mathematical functions. It’s a fundamental package for anyone planning to do any scientific computing in the Python programming language.

What is NumPy?

The NumPy library allows Python users to perform high-level scientific computing and manipulate arrays. It offers a variety of mathematical applications such as basic arithmetic, linear algebra, statistical analysis, and other functions optimized to operate on arrays.

Professionals who use NumPy to work with data may also rely on other libraries to perform analyses. NumPy integrates with libraries like SciPy, pandas, and Matplotlib to provide users with a comprehensive tool set when working with different data formats.

As an open-source software, NumPy is free to use. Its accessibility and ease of use make it a suitable choice for beginners. Learning how to leverage its vast capabilities can expand your career opportunities and bring greater efficiency to your data-related work.

Numpy | Introduction Image Description

Maximize your potential

Sign up for special offers, career resources, and recommendations that will help you grow, prepare, and advance in your career.

NumPy course curriculum

Before you start learning how to use NumPy, it can help to first have some experience with the Python programming language. From there, you can take a course that covers the basics of the NumPy library:

  • Installing NumPy

  • Reading through NumPy’s documentation

  • Creating arrays

  • Performing mathematical operations

  • Using boolean indexing and filtering

Once you feel comfortable with these introductory concepts, you can move on to more advanced topics, such as linear algebra operations, random number generation, and working with structured arrays. Depending on your chosen educational path, you may have opportunities to apply your new skills to practice projects.

Learning how to use NumPy can supplement your knowledge of data analysis and computer science. edX offers a variety of educational opportunities for learners interested in studying these topics, as well as a host of other disciplines. A boot camp can provide flexible hands-on learning for those who want to upskill quickly, while executive education courses are designed for busy professionals. You can also pursue a more comprehensive curriculum in a bachelor’s degree program or, for more advanced learners, a master’s degree program. Find the right learning path for you.

Explore jobs that use NumPy

Because of its vast capabilities in handling data, NumPy is a great tool for anyone who works with large amounts of information. Here are a few roles that can directly benefit from experience using NumPy:

  • Data scientist: Uses NumPy for performing statistical analysis, implementing machine learning algorithms, and visualizing data.Footnote 1

  • Quantitative analyst: Uses NumPy for time series analysis, risk assessment, and developing trading algorithms.Footnote 2

  • Research scientist: Uses NumPy for numerical simulations, data analysis, modeling, conducting experiments, and analyzing results.Footnote 3

  • Astronomer: Uses NumPy for data processing and analysis, image manipulation, data reduction, and statistical analysis of celestial observations.Footnote 4

  • Quality assurance (QA) engineer: Uses NumPy for data analysis and validation when testing software.Footnote 5

While many of these roles exist within similar industries, employment qualifications for careers that use NumPy may differ based on the position and employer. Some roles may require a higher level degree while others may only ask for a demonstration of skills that can be acquired in a data analytics boot camp, for example. Before deciding on which learning path will work best for you, research potential roles you hope to pursue and align your coursework with your professional aspirations.