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    • Linear Algebra

    Linear Algebra Courses Online

    Study linear algebra for mathematical and engineering applications. Learn about matrices, vectors, and linear transformations.

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    Explore the Linear Algebra Course Catalog

    • Status: Free
      Free
      K

      Korea Advanced Institute of Science and Technology(KAIST)

      Differential Equations Part I Basic Theory

      Skills you'll gain: Differential Equations, Mathematical Modeling, Applied Mathematics, Calculus, Linear Algebra, Vibrations, Mechanics

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    • I

      Imperial College London

      Mathematics for Machine Learning: Multivariate Calculus

      Skills you'll gain: Regression Analysis, Calculus, Advanced Mathematics, Machine Learning Algorithms, Statistical Analysis, Linear Algebra, Artificial Neural Networks, Python Programming, Derivatives

      4.7
      Rating, 4.7 out of 5 stars
      ·
      5.7K reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free
      Free
      D

      Duke University

      Data Science Math Skills

      Skills you'll gain: Probability, Bayesian Statistics, General Mathematics, Calculus, Graphing, Statistics, Data Science, Data Analysis, Plot (Graphics), Algebra, Geometry, Arithmetic, Derivatives

      4.5
      Rating, 4.5 out of 5 stars
      ·
      13K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Introduction to Neural Networks and PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Deep Learning, Predictive Modeling, Probability & Statistics, Machine Learning, Regression Analysis, Data Manipulation, Linear Algebra

      4.4
      Rating, 4.4 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of California, Santa Cruz

      Bayesian Statistics

      Skills you'll gain: Time Series Analysis and Forecasting, Bayesian Statistics, R Programming, Forecasting, Statistical Inference, Statistical Modeling, Technical Communication, Data Analysis, Probability, Statistical Machine Learning, Statistical Methods, Statistical Analysis, Advanced Analytics, Mathematical Modeling, Microsoft Excel, Markov Model, Probability Distribution, Probability & Statistics, Unsupervised Learning, Regression Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      3.5K reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      U

      Universidad Nacional Autónoma de México

      Álgebra básica

      Skills you'll gain: Algebra, General Mathematics, Arithmetic, Applied Mathematics, Geometry

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.6K reviews

      Mixed · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Calculus for Machine Learning and Data Science

      Skills you'll gain: Applied Mathematics, Calculus, Numerical Analysis, Mathematical Modeling, Machine Learning, Python Programming, Regression Analysis, Artificial Neural Networks, Deep Learning, Derivatives

      4.8
      Rating, 4.8 out of 5 stars
      ·
      840 reviews

      Intermediate · Course · 1 - 4 Weeks

    • H

      Howard University

      Fundamental Linear Algebra Concepts with Python

      Skills you'll gain: Linear Algebra, NumPy, Applied Mathematics, Numerical Analysis, Algebra, Python Programming, Data Manipulation

      4.4
      Rating, 4.4 out of 5 stars
      ·
      15 reviews

      Mixed · Course · 1 - 4 Weeks

    • I

      IBM

      Exploratory Data Analysis for Machine Learning

      Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Data Cleansing, Data Access, Data Analysis, Statistical Inference, Statistical Hypothesis Testing, Data Quality, Data Science, Probability & Statistics, Jupyter, Machine Learning, Data Manipulation, Pandas (Python Package), Statistical Analysis, Data Transformation, Artificial Intelligence

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.2K reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free
      Free
      S

      Stanford University

      Introduction to Logic

      Skills you'll gain: Logical Reasoning, Computational Logic, Deductive Reasoning, Computational Thinking, Business Logic, Functional Design, Algorithms

      4.4
      Rating, 4.4 out of 5 stars
      ·
      647 reviews

      Intermediate · Course · 1 - 3 Months

    • J

      Johns Hopkins University

      Algebra: Elementary to Advanced - Equations & Inequalities

      Skills you'll gain: Algebra, Arithmetic, Mathematical Modeling, Applied Mathematics, Graphing, Probability & Statistics

      4.8
      Rating, 4.8 out of 5 stars
      ·
      583 reviews

      Beginner · Course · 1 - 3 Months

    • V

      Vanderbilt University

      Introduction to Data, Signal, and Image Analysis with MATLAB

      Skills you'll gain: Data Visualization, Image Analysis, Data Visualization Software, Machine Learning Methods, Matlab, Applied Machine Learning, Statistical Methods, Data Analysis, Data Processing, Computer Vision, Regression Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      218 reviews

      Intermediate · Course · 1 - 3 Months

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    1234…55

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

    • Differential Equations Part I Basic Theory: Korea Advanced Institute of Science and Technology(KAIST)
    • Mathematics for Machine Learning: Multivariate Calculus: Imperial College London
    • Data Science Math Skills: Duke University
    • Introduction to Neural Networks and PyTorch: IBM
    • Bayesian Statistics: University of California, Santa Cruz
    • Álgebra básica: Universidad Nacional Autónoma de México
    • Calculus for Machine Learning and Data Science: DeepLearning.AI
    • Fundamental Linear Algebra Concepts with Python: Howard University
    • Exploratory Data Analysis for Machine Learning: IBM
    • Introduction to Logic: Stanford University

    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 Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Linear Algebra

    Linear algebra courses on Coursera cover a wide array of fundamental and advanced topics, enabling learners to:

    • Understand vectors and matrices and their applications in various fields
    • Learn methods for solving systems of linear equations
    • Explore eigenvalues and eigenvectors and their significance in transformations
    • Apply linear algebra concepts to computer graphics, data analysis, and more
    • Discover how linear algebra supports machine learning and artificial intelligence algorithms‎

    No prior experience in advanced mathematics is required to start with the introductory linear algebra courses available on Coursera. These courses are designed to accommodate learners at different proficiency levels:

    • Beginners can start with basic concepts of vectors and matrix operations.
    • Intermediate learners can delve into more complex subjects such as linear transformations and space.
    • Advanced learners can tackle topics like abstract vector spaces and computational linear algebra.‎

    Coursera offers various credentials through its linear algebra courses, designed to cater to both novices and professionals:

    • Course certificates that validate your knowledge of linear algebra fundamentals
    • Professional certificates that demonstrate your specialized skills in mathematics
    • Specializations with focused expertise in advanced linear algebra topics‎

    Looking to enhance your team's linear algebra skills? Coursera provides tailored enterprise solutions for teams ranging of 5-125 employees. Our offerings include advanced analytics, customized learning paths, and collaborative tools. To explore our linear algebra training options and make a purchase, please visit our Coursera for Teams page.‎

    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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