Python
Numpy
Linear Algebra
Data Analysis
Exercises and examples for linear algebra using Python and NumPy, covering topics such as vectors, matrices, and linear transformations.
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Difficulty
beginner
Average duration
5 hrs
Difficulty
beginner
Average duration
5 hrs
Difficulty
beginner
Average duration
5 hrs
Difficulty
beginner
Average duration
5 hrs
Difficulty
beginner
Average duration
5 hrs
Difficulty
beginner
Average duration
5 hrs
In this tutorial, you will learn to manipulate vectors and matrices in Python using both nested lists and NumPy arrays. We will explore from basic operations to more advanced ones. To ensure you understand both ways of working with data in Python, we will divide the project into two parts:
By the end of this tutorial, you will be able to perform calculations with vectors and matrices in Python efficiently and understand when it is better to use each approach.
Each exercise is a small Python application that contains the following files:
Note: These exercises have automatic grading. The tests are very rigid and strict; my recommendation is not to pay too much attention to the tests and use them only as a suggestion, or you might get frustrated.
This project follows the all-contributors specification. All contributions are welcome!
This and many other exercises are built by students as part of the 4Geeks Academy Coding Bootcamp by Alejandro Sánchez and many other contributors. Find out more about our Full Stack Developer Course, and Data Science Bootcamp.
Difficulty
beginner
Average duration
5 hrs
Difficulty
beginner
Average duration
5 hrs