https://github.com/labex-labs/numpy-for-beginners

This comprehensive course covers the fundamental concepts and practical techniques of NumPy, the essential library for numerical computing in Python. Learn to create, manipulate, and analyze arrays efficiently.
https://github.com/labex-labs/numpy-for-beginners

challenges course exercises hands-on labex labs numpy playground programming python

Last synced: 4 months ago
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This comprehensive course covers the fundamental concepts and practical techniques of NumPy, the essential library for numerical computing in Python. Learn to create, manipulate, and analyze arrays efficiently.

• Host: GitHub
• URL: https://github.com/labex-labs/numpy-for-beginners
• Owner: labex-labs
• Created: 2025-09-10T08:49:27.000Z (4 months ago)
• Default Branch: master
• Last Pushed: 2025-09-10T08:49:52.000Z (4 months ago)
• Last Synced: 2025-09-10T12:11:00.040Z (4 months ago)
• Topics: challenges, course, exercises, hands-on, labex, labs, numpy, playground, programming, python
• Homepage: https://labex.io/courses/numpy-for-beginners
• Size: 18.6 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# NumPy for Beginners

## Languages

🇨🇳 [简体中文](README_zh.md) 🇪🇸 [Español](README_es.md) 🇫🇷 [Français](README_fr.md) 🇩🇪 [Deutsch](README_de.md) 🇯🇵 [日本語](README_ja.md) 🇷🇺 [Русский](README_ru.md) 🇰🇷 [한국어](README_ko.md) 🇧🇷 [Português](README_pt.md) 🇺🇸 [English](README.md) 

[![NumPy for Beginners](https://cover-creator.labex.io/numpy-for-beginners.png)](https://labex.io/courses/numpy-for-beginners)

[![Start-Learning](https://img.shields.io/badge/Start-Learning-whitesmoke?style=for-the-badge)](https://labex.io/courses/numpy-for-beginners)

This comprehensive course covers the fundamental concepts and practical techniques of NumPy, the essential library for numerical computing in Python. Learn to create, manipulate, and analyze arrays efficiently.

![NumPy](https://img.shields.io/badge/NumPy-whitesmoke?style=for-the-badge&logo=numpy)

![Python](https://img.shields.io/badge/Python-whitesmoke?style=for-the-badge&logo=python)

## Exercises

|   Index | Name                             | Difficulty   | Practice                                                                                                   |

|---------|----------------------------------|--------------|------------------------------------------------------------------------------------------------------------|

|       1 | 📖 🆓 NumPy Array Creation       | Beginner     | Start Lab       |

|       2 | 📖 🆓 NumPy Indexing on ndarrays | Beginner     | Start Lab |

|       3 | 📖 🆓 NumPy IO Genfromtxt        | Beginner     | Start Lab        |

|       4 | 📖 🆓 NumPy Data Types           | Beginner     | Start Lab           |

|       5 | 📖 🆓 NumPy Broadcasting         | Beginner     | Start Lab         |

|       6 | 📖 🆓 NumPy Copies and Views     | Beginner     | Start Lab     |

|       7 | 📖 🆓 NumPy Structured Arrays    | Beginner     | Start Lab    |

|       8 | 📖 🆓 NumPy Universal Functions  | Beginner     | Start Lab  |

## Environment

LabEx is an interactive, hands-on learning platform dedicated to coding and technology. It combines labs, AI assistance, and virtual machines to provide a no-video, practical learning experience.

![](https://tutorial-screenshot.getvm.io/images/vm-1725247253.png)

- A strict "Learn by Doing" approach with exclusive hands-on labs and no videos.

- Interactive online environments within the browser, with automated step-by-step checks.

- A structured content organization with the Skill Tree based learning system.

- A growing learning resource of 30 Skill Trees and over 6,000 Labs.

- The learning assistant Labby, built on lastest AI models, providing a conversational learning experience.

Learn more about [LabEx VM](https://support.labex.io/using-labex/virtual-machine).

## More

- 🔗 [NumPy Programming Courses](https://github.com/labex-labs/awesome-programming-courses)

- 🔗 [NumPy Programming Projects](https://github.com/labex-labs/awesome-programming-projects)

- 🔗 [NumPy Free Tutorials](https://github.com/labex-labs/numpy-free-tutorials)