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147 learners

Eigenvalues, Eigenvectors, and Diagonalization with NumPy

This course introduces students to eigenvalues, eigenvectors, and matrix diagonalization. Focusing on matrix transformations, students will explore practical applications of these concepts using the `numpy.linalg` library to solidify their understanding of advanced linear algebra principles.

Numpy

Python

See path

5 lessons

25 practices

3 hours

Mathematics and Statistics

Course details

Introduction to Eigenvalues and Eigenvectors with NumPy

Preview

Eigenvalues and Eigenvectors in NumPy

Explore Matrix Changes Impact

Fix the Matrix Calculation Errors

Calculate Eigenvalues and Eigenvectors

Write Your First NumPy Matrix Code

Previous Course

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Francisco Aguilar Meléndez

Data Scientist

+11

From our community

Hear what our customers have to say about CodeSignal Learn

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11

I love that it's personalized. When I'm stuck, I don't have to hope my Google searches come out successful. The AI mentor Cosmo knows exactly what I need.

Faith Yim

Software Engineer

+14

It's an amazing product and exceeded my expectations, helping me prepare for my job interviews. Hands-on learning requires you to actually know what you are doing.

Alex Bush

Full Stack Engineer

I'm really impressed by the AI tutor Cosmo's feedback about my code. It's honestly kind of insane to me that it's so targeted and specific.

Abbey Helterbran

Tech consultant

I tried Leetcode but it was too disorganized. CodeSignal covers all the topics I'm interested in and is way more structured.

Jonathan Miller

Senior Machine Learning Engineer

+12

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11