Introducing Python Libraries: SciPy and NumPy

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Last updated on June 17, 2026 11:48 am

Learn how to use the Python libraries SciPy and NumPy to carry out complex mathematical and scientific data operations in this Python programming tutorial.

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NumPy and SciPy are important Python libraries that perform various functions and processes. NumPy refers to ?numerical Python?, while SciPy refers to ?scientific Python?. These Python libraries are employed to carry out various data operations. This course will enable you to learn scientific Python in a very accessible and practical way. Register for this course to discover how to design and carry out complex computing functions immediately.

What You Will Learn In This Free Course

  • Explain the role of Python libraries…
  • Outline the benefits of Python libra…
  • Recognise when to choose one Python …
  • List the steps involved in installin…
  • Explain the role of Python libraries SciPy and NumPy
  • Outline the benefits of Python libraries SciPy and NumPy
  • Recognise when to choose one Python library over the other
  • List the steps involved in installing SciPy and NumPy
  • Describe the reasons to use SciPy to perform complex functions, integrals, statistics and linear algebra
  • Identify the ways to use NumPy for calculating Eigenvalues, determinants and covariance
  • Python SciPy and NumPy

    This module will teach you about the Python libraries SciPy and NumPy. You will explore the benefits of both SciPy and NumPy, as well as how and when to utilise them.

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