Introduction to Linear Algebra and Python

Dennis Davenport introduces the mathematical objects behind small data problems, then uses Python to work with them. The sequence covers matrices, vector equations and applications rather than starting with a long abstract proof course. Software setup is part of the published outline, making the relationship between a calculation and its notebook representation a useful comparison point.

What you will learn

• Represent a small dataset as a matrix.
• Use Python to examine vector equations.
• Connect a system of equations with a data problem.

Who this suits

Consider this if you want a first computational introduction to linear algebra. Allow time to install and become comfortable with the notebook tools.

Before you enroll

The beginner label does not remove the need for careful algebra. Keep handwritten calculations alongside the code so a successful function call does not conceal a misunderstood operation.

Coursera lists paid enrollment or subscription access. Check the enrollment screen for included assessments, certificate terms, trials and any financial-aid options. University authorship does not by itself confer admission, academic credit or a professional license.

Put it into practice

Model two products using a small table of ingredient requirements. Express one production target as a vector equation and explain what each row and column represents.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

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