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⇱ Python Data Science: NumPy | Coursera

Python Data Science: NumPy

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Python Data Science: NumPy

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Gain insight into a topic and learn the fundamentals.
4 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • In this course, you will manage and analyze data with NumPy arrays, and manipulate and modify data with NumPy arrays.

Details to know

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Recently updated!

January 2026

Assessments

1 assignment

Taught in English

Build your subject-matter expertise

This course is part of the Using Data Science Tools in Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

In this course, you'll continue developing your data science skills in Python by working with one of the most fundamental data science libraries—NumPy. You'll create NumPy arrays, load and save NumPy data, and analyze data in arrays. You'll also manipulate and modify data in those arrays.

This is the second course in a multi-course Specialization. All of the courses in this Specialization require that you use the provided virtual machine, which includes an installation of Python and data science libraries. The course setup instructions provided in the first course go into more detail about the hardware and software requirements.

The foundation of data science in Python® is NumPy. Most of your work will involve NumPy, whether directly or indirectly. So, you'll leverage the power of this library to manage your data and extract useful insights from that data.

What's included

1 reading5 plugins

1 reading•Total 5 minutes
  • ⚠️READ THIS FIRST⚠️•5 minutes
5 plugins•Total 115 minutes
  • Lesson Introduction•5 minutes
  • Create NumPy Arrays•35 minutes
  • Load and Save NumPy Data•35 minutes
  • Analyze Data in NumPy Arrays•35 minutes
  • Lesson Summary•5 minutes

While analyzing data is an important part of the data science process, so is changing that data to meet your needs. Whether it's to prepare and clean the data, or to modify it for easier analysis and presentation, being able to transform your NumPy arrays is crucial.

What's included

4 plugins

4 plugins•Total 130 minutes
  • Lesson Introduction•5 minutes
  • Manipulate Data in NumPy Arrays•60 minutes
  • Modify Data in NumPy Arrays•60 minutes
  • Lesson Summary•5 minutes

You'll wrap things up and then validate what you've learned in this course by taking an assessment.

What's included

1 reading1 assignment

1 reading•Total 5 minutes
  • Course Summary•5 minutes
1 assignment•Total 10 minutes
  • Course Assessment•10 minutes

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Instructor

Logical Operations
158 Courses•37,588 learners

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