Master linear algebra: theory and implementation in code

Learn concepts in linear algebra and matrix analysis, and implement them in MATLAB and Python.

4.73 (4924 reviews)

Udemy

platform

English

language

Math

What you will learn

Understand theoretical concepts in linear algebra, including proofs

Implement linear algebra concepts in scientific programming languages (MATLAB, Python)

Apply linear algebra concepts to real datasets

Ace your linear algebra exam!

Apply linear algebra on computers with confidence

Gain additional insights into solving problems in linear algebra, including homeworks and applications

Be confident in learning advanced linear algebra topics

Understand some of the important maths underlying machine learning

The math underlying most of AI (artificial intelligence)

Course Gallery

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Comidoc Review

Our Verdict

This 34-hour course by Mike Cohen offers an engaging, comprehensive exploration of linear algebra theory and implementation in code, with a focus on practical applications. While catering to a wide range of learners—from beginners to advanced professionals—this course may initially feel tedious for some due to its gradual buildup towards complex topics. However, the reward lies in an enriched understanding of matrix analysis and applicable MATLAB/Python skills that serve as solid groundwork for tackling more advanced analytical methods like PCA and GED.

What We Liked

Covers theoretical concepts in linear algebra with proofs
Implements linear algebra concepts in MATLAB and Python
Applies linear algebra concepts to real datasets
Incorporates long-tail keywords like 'scientific programming languages', 'real datasets', and 'geometric thinking'

Potential Drawbacks

May be more practical than theoretical for some learners' preferences
Can feel overwhelming for those without basic coding skills
Requires pencil-and-paper work despite its modern approach
Lacks a more intuitive explanation of certain complex concepts like eigen decomposition