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    • Linear Algebra
    Related topics:calculuslinear differential equationmathmathematicsalgebraibm

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    165 results for "linear algebra"

    • Imperial College London

      Imperial College London

      Mathematics for Machine Learning

      Skills you'll gain: Algebra, Algorithms, Analysis, Artificial Neural Networks, Basic Descriptive Statistics, Calculus, Computer Programming, Data Analysis, Deep Learning, Differential Equations, General Statistics, Linear Algebra, Linear Regression, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Programming, Theoretical Computer Science

      4.6

      (12.8k reviews)

      Beginner · Specialization

    • Imperial College London

      Imperial College London

      Mathematics for Machine Learning: Linear Algebra

      Skills you'll gain: Mathematics, Python Programming, Matrices, Statistical Programming, Linearity, Computer Programming, Algebra, Machine Learning, Machine Learning Algorithms, Linear Algebra

      4.7

      (10.8k reviews)

      Beginner · Course

    • University of Colorado Boulder

      University of Colorado Boulder

      Essential Linear Algebra for Data Science

      Skills you'll gain: Mathematics, Mathematical Theory & Analysis, Algebra, Linear Algebra

      4.8

      (25 reviews)

      Intermediate · Course

    • Johns Hopkins University

      Johns Hopkins University

      Algebra: Elementary to Advanced

      Skills you'll gain: Algebra, Linear Algebra, Mathematics

      4.8

      (227 reviews)

      Beginner · Specialization

    • The Hong Kong University of Science and Technology

      The Hong Kong University of Science and Technology

      Mathematics for Engineers

      Skills you'll gain: Algebra, Calculus, Data Analysis, Data Analysis Software, Differential Equations, Linear Algebra, Mathematical Theory & Analysis, Mathematics, Modal Μ-Calculus

      4.8

      (6.1k reviews)

      Beginner · Specialization

    • Korea Advanced Institute of Science and Technology(KAIST)

      Korea Advanced Institute of Science and Technology(KAIST)

      Math for AI beginner part 1 Linear Algebra

      Skills you'll gain: Mathematics, Algebra, Linear Algebra

      4.9

      (7 reviews)

      Beginner · Course

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      The Hong Kong University of Science and Technology

      The Hong Kong University of Science and Technology

      Matrix Algebra for Engineers

      Skills you'll gain: Mathematics, Linearity, Matrices, Linear Algebra, Algebra

      4.9

      (3.6k reviews)

      Beginner · Course

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      Free

      Duke University

      Duke University

      Data Science Math Skills

      Skills you'll gain: Theoretical Computer Science, Mathematics, Plot (Graphics), Mathematical Theory & Analysis, Bayesian Statistics, Probability & Statistics, General Statistics, Graph Theory, Data Visualization, Probability Distribution, Bayesian, Probability, Computational Logic, Algebra

      4.5

      (10.3k reviews)

      Beginner · Course

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      Free

      University of Minnesota

      University of Minnesota

      Matrix Methods

      Skills you'll gain: Mathematical Theory & Analysis, Entrepreneurship, Mathematics, Analysis, Linearity, Linear Algebra, Algebra, Matrices

      4.1

      (209 reviews)

      Intermediate · Course

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      University of Colorado Boulder

      University of Colorado Boulder

      Expressway to Data Science: Essential Math

      Skills you'll gain: Algebra, Big Data, Calculus, Data Analysis, Data Management, Data Mining, Data Model, Data Structures, Design and Product, Linear Algebra, Mathematical Theory & Analysis, Mathematics, Probability & Statistics, Probability Distribution, Product Design, Software Architecture, Software Engineering, Theoretical Computer Science

      4.4

      (52 reviews)

      Intermediate · Specialization

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      Free

      University of North Texas

      University of North Texas

      College Math Prep

      Skills you'll gain: Leadership and Management, Mathematics, Financial Accounting, Entrepreneurship, Probability & Statistics, Graph Theory, Accounting, Linear Algebra, Algebra, Research and Design, Problem Solving

      4.1

      (30 reviews)

      Beginner · Course

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      Johns Hopkins University

      Johns Hopkins University

      Precalculus through Data and Modelling

      Skills you'll gain: Algebra, Calculus, Data Analysis, Data Management, Data Model, Geometry, Linear Algebra, Mathematical Theory & Analysis, Mathematics, Probability & Statistics

      4.6

      (153 reviews)

      Beginner · Specialization

    Searches related to linear algebra

    essential linear algebra for data science
    mathematics for machine learning: linear algebra
    math for ai beginner part 1 linear algebra
    doğrusal cebir i: uzaylar ve işlemciler / linear algebra i: spaces and operators
    doğrusal cebir ii: kare matrisler, hesaplama yöntemleri ve uygulamalar / linear algebra ii: square matrices, calculation methods and applications
    aprendiendo python con álgebra lineal
    1234…14

    In summary, here are 10 of our most popular linear algebra courses

    • Mathematics for Machine Learning: Imperial College London
    • Mathematics for Machine Learning: Linear Algebra: Imperial College London
    • Essential Linear Algebra for Data Science: University of Colorado Boulder
    • Algebra: Elementary to Advanced: Johns Hopkins University
    • Mathematics 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)
    • Matrix Algebra for Engineers: The Hong Kong University of Science and Technology
    • Data Science Math Skills: Duke University
    • Matrix Methods: University of Minnesota
    • Expressway to Data Science: Essential Math: University of Colorado Boulder

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about 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.‎

    • 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.‎

    • 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.‎

    • 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.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
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