What is linear algebra?

Linear algebra is a central branch of mathematics that is focused on the interaction between vector spaces, linear equations, matrices, and linear transformations. Linear algebra is similar to basic algebra, but instead of finding correlations between single numbers, it seeks to find linear connections between scalars (temperature, mass, volume, speed) and vectors, which are lists of numbers. Linear algebra is important for the worlds of data analytics and any kind of work in the computer software field, as it builds on mathematical logic and building block relationships.

Why is it important to learn linear algebra?

It's important to learn linear algebra to get deeper clarity and better intuition for how mathematical algorithms really work. This knowledge can help you think more logically about projects and apply the linear algebra principles to machine learning projects you may be moving toward. Overall, having linear algebra knowledge can help you learn the fundamentals of data analysis, machine learning, and mathematical theory.

What are typical careers that use linear algebra?

Typical careers that use knowledge of linear algebra involve jobs in physics and science, data analysis, technology operations and management, machine learning, and algebra instruction. All of these careers are in high demand, as the world gets more connected through data systems.

How can taking online courses help me learn linear algebra?

When you take online courses about linear algebra, you can learn how mathematical relationships matter in classifying objects, spaces, and situations. The knowledge you can gain by studying linear algebra can give you insights into different fields like economics, physics, and politics. For example, the concepts of linear algebra can be found in determining local auto traffic depending on people's moving patterns and analyzing how this movement matters to local business factors.

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198 resultados referentes a "linear algebra"

Imperial College London
Mathematics for Machine Learning
Habilidades que você terá: Algebra, Algorithms, Analysis, Artificial Neural Networks, Basic Descriptive Statistics, Calculus, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Deep Learning, Differential Equations, Dimensionality Reduction, General Statistics, Lambda Calculus, Linear Algebra, Linearity, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Matrices, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Programming, Theoretical Computer Science
4.6
(13k avaliações)
Beginner · Specialization · 3-6 Months
University of Colorado Boulder
Essential Linear Algebra for Data Science
Habilidades que você terá: Mathematics, Linear Algebra, Entrepreneurship, Computer Graphic Techniques, Problem Solving, Leadership and Management, Mathematical Theory & Analysis, Research and Design, Probability & Statistics, General Statistics, Computer Graphics, Algebra, Linearity
4.7
(48 avaliações)
Intermediate · Course · 1-3 Months
Gratuito
Imperial College London
Mathematics for Machine Learning: Multivariate Calculus
Habilidades que você terá: Deep Learning, Mathematics, Computer Programming, Linear Algebra, Machine Learning, Differential Equations, Mathematical Theory & Analysis, Theoretical Computer Science, Machine Learning Algorithms, Regression, Probability & Statistics, Algebra, Calculus, Lambda Calculus, Linearity, Artificial Neural Networks, Algorithms, Mathematical Optimization, Linear Regression
4.7
(5.2k avaliações)
Beginner · Course · 1-3 Months
Arizona State University
AI and Machine Learning MasterTrack® Certificate
Habilidades que você terá: Tableau Software, Finance, Communication, Hardware Design, Statistical Programming, Computational Logic, Software Architecture, Software Testing, Computer Networking, Probability & Statistics, Algorithms, System Security, Security Engineering, SQL, Deep Learning, Data Analysis, Other Programming Languages, Machine Learning, Project, Geovisualization, Entrepreneurship, Databases, Programming Principles, Statistical Tests, Euler'S Totient Function, Data Visualization, Bayesian Network, Mobile Development, Theoretical Computer Science, General Statistics, BlockChain, Strategy and Operations, Operating Systems, Feature Engineering, Software Engineering, Data Mining, Network Security, Software
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Mastertrack · 6-12 Months

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Em resumo, aqui estão 10 dos nossos cursos mais populares linear algebra

Mathematics for Machine Learning: Imperial College London
Linear Algebra for Data Science Using Python: Howard University
Mathematics for Machine Learning: Linear Algebra: Imperial College London
Mathematics for Engineers: The Hong Kong University of Science and Technology
Algebra: Elementary to Advanced: Johns Hopkins University
Essential Linear Algebra for Data Science: University of Colorado Boulder
Matrix Algebra for Engineers: The Hong Kong University of Science and Technology
Math for AI beginner part 1 Linear Algebra: Korea Advanced Institute of Science and Technology(KAIST)
Data Science Math Skills: Duke University
Mathematics for Machine Learning: Multivariate Calculus: Imperial College London

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Perguntas frequentes sobre Álgebra linear

Linear algebra is a central branch of mathematics that is focused on the interaction between vector spaces, linear equations, matrices, and linear transformations. Linear algebra is similar to basic algebra, but instead of finding correlations between single numbers, it seeks to find linear connections between scalars (temperature, mass, volume, speed) and vectors, which are lists of numbers. Linear algebra is important for the worlds of data analytics and any kind of work in the computer software field, as it builds on mathematical logic and building block relationships.‎
It's important to learn linear algebra to get deeper clarity and better intuition for how mathematical algorithms really work. This knowledge can help you think more logically about projects and apply the linear algebra principles to machine learning projects you may be moving toward. Overall, having linear algebra knowledge can help you learn the fundamentals of data analysis, machine learning, and mathematical theory.‎
When you take online courses about linear algebra, you can learn how mathematical relationships matter in classifying objects, spaces, and situations. The knowledge you can gain by studying linear algebra can give you insights into different fields like economics, physics, and politics. For example, the concepts of linear algebra can be found in determining local auto traffic depending on people's moving patterns and analyzing how this movement matters to local business factors.‎

Este conteúdo de Perguntas frequentes foi disponibilizado apenas para fins informativos. Os aprendizes são aconselhados a realizar pesquisas adicionais para garantir que os cursos e outras credenciais buscadas atendam a seus objetivos pessoais, profissionais e financeiros.