EdX

Applications of Linear Algebra Part 1 (edX)

Applications of Linear Algebra Part 1 (edX)

Learn to use linear algebra in computer graphics by making images disappear in an animation or creating a mosaic or fractal and in data mining to measure similarities between movies, songs, or friends. From simulating complex phenomenon on supercomputers to storing the coordinates needed in modern 3D printing, data is a huge and growing part of our world.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

A major tool to manipulate and study this data is linear algebra. This course is part 1 of a 2-part course. In this part, we’ll learn basics of matrix algebra with an emphasis on application. This class has a focus on computer graphics while also containing examples in data mining.

We’ll learn to make an image transparent, fade from one image to another, and rotate a 3D wireframe model. We’ll also mine data; for example, we will find similar movies that one might enjoy seeing. In the topic of sports ranking, we’ll be ready to participate in March Madness and submit our own mathematically generated brackets to compete against millions of others. The lectures are developed to encourage you to explore and create your own ideas either through your own programming but also with online tools developed for the course. Come to this course ready to investigate your own ideas.
What you'll learn

  • Fundamental mathematical operations on matrices such as matrix arithmetic, norms, and solving linear systems
  • Applications of linear algebra in data mining such as finding similar elements in a dataset using measure of distance, a method to recognize handwritten numbers using matrix norms, and ranking sports teams
  • Applications of linear algebra in computer graphics such as visually approximating an image with a page of typed characters, blending images, and creating composite images.
  • Explore applications with online codes.
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Linear Models and Matrix Algebra (edX) EdX
HarvardX,Harvard University

Introduction to Linear Models and Matrix Algebra (edX)

Learn to use R programming to apply linear models to analyze data in life sciences. Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory data analysis course, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. We perform statistical inference on these differences. Throughout the course we will use the R programming language.

Self Paced
Self-Paced
Algèbre Linéaire (Partie 3) (edX) EdX
École Polytechnique Fédérale de Lausanne,EPFLx

Algèbre Linéaire (Partie 3) (edX)

Un MOOC francophone d'algèbre linéaire accessible à tous, enseigné de manière rigoureuse et ne nécessitant aucun prérequis. Vous voulez apprendre l'algèbre linéaire, un précieux outil complémentaire à vos connaissances acquises durant vos études en économie, ingénierie, physique, ou statistique? Ou simplement pour la beauté de la matière? Alors ce cours est fait pour vous!

Self Paced
Self-Paced
Introducción a Matemáticas para Finanzas y Negocios (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Introducción a Matemáticas para Finanzas y Negocios (edX)

El objetivo del curso es entender como ciertos conceptos matemáticos se utilizan de forma recurrente para analizar problemas financieros y de negocios. En la primera parte del curso se analiza el caso de las funciones lineales donde se introduce el concepto de pendiente para cuantificar la dependencia entre las variables.

Self Paced
Self-Paced
Introduction to Bayesian Statistics Using R (edX) EdX
University of Canterbury,UCx

Introduction to Bayesian Statistics Using R (edX)

Learn the fundamentals of Bayesian approach to data analysis, and practice answering real life questions using R. Basics of Bayesian Data Analysis Using R is part one of the Bayesian Data Analysis in R professional certificate. Bayesian approach is becoming increasingly popular in all fields of data analysis, including but not limited to epidemiology, ecology, economics, and political sciences. It also plays an increasingly important role in data mining and deep learning. Let this course be your first step into Bayesian statistics.

Self Paced
Self-Paced
MathTrackX: Differential Calculus (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Differential Calculus (edX)

Discover concepts and techniques relating to differentiation and how they can be applied to solve real world problems. This course will cover basic concepts and techniques relating to differentiation; a fundamental tool of calculus. Derivatives are key to the understanding of rates of change, that is the extent to which a function responds to changes in a dependent variable.

Self Paced
Self-Paced
MathTrackX: Statistics (edX) EdX
University of Adelaide,AdelaideX

MathTrackX: Statistics (edX)

Understand fundamental concepts relating to statistical inference and how they can be applied to solve real world problems. This course will build on probability and random variable knowledge gained from previous courses in the MathTrackX XSeries with the study of statistical inference, one of the most important parts of statistics.

Self Paced
Self-Paced
Computing for Data Analysis (edX) EdX
Georgia Institute of Technology,GTx

Computing for Data Analysis (edX)

A hands-on introduction to basic programming principles and practice relevant to modern data analysis, data mining, and machine learning. The modern data analysis pipeline involves collection, preprocessing, storage, analysis, and interactive visualization of data. In the course, you’ll see how computing and mathematics come together.

Aug 24th 2026
13-24 Weeks
Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD (edX) EdX
Georgia Institute of Technology,GTx

Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD (edX)

This course takes you through roughly five weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. In the first part of this course you will explore methods to compute an approximate solution to an inconsistent system of equations that have no solutions. Our overall approach is to center our algorithms on the concept of distance.

Self Paced
Self-Paced
Introduction to Computer Science and Programming (edX) EdX
Tokyo Institute of Technology,TokyoTechX

Introduction to Computer Science and Programming (edX)

The term “Computation” refers to the action performed by a computer. A computation can be a basic operation and it can also be a sophisticated computer simultation requiring a large amount of data and substantial resources. This course aims at introducing learners with no prior knowledge to basics and key concepts of computer science. By following the lectures and exercises of this course you will have an understanding of algorithms and you will get a real experience of programming using the language Ruby.

Self Paced
Self-Paced