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  • Linear Algebra For Machine Learning

Linear Algebra for Machine Learning Courses

Linear Algebra for Machine Learning courses can help you learn matrix operations, vector spaces, eigenvalues, and linear transformations. You can build skills in solving systems of equations, dimensionality reduction, and understanding data representations. Many courses introduce tools like NumPy and MATLAB, that support implementing algorithms and performing computations efficiently in AI and machine learning projects.


Popular Linear Algebra for Machine Learning Courses and Certifications


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    Coursera

    Foundations of Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Unsupervised Learning, Data Preprocessing, Time Series Analysis and Forecasting, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting, Decision Tree Learning, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling

    4.6
    Rating, 4.6 out of 5 stars
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    11 reviews

    Intermediate · Course · 1 - 4 Weeks

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    Coursera

    ML Concepts, Models & Workflow Essentials

    Skills you'll gain: Java Programming, Java, Feature Engineering, Deep Learning, Data Pipelines

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
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    DeepLearning.AI

    Probability & Statistics for Machine Learning & Data Science

    Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Statistical Modeling, Exploratory Data Analysis, Statistical Visualization

    4.6
    Rating, 4.6 out of 5 stars
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    678 reviews

    Intermediate · Course · 1 - 4 Weeks

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    IBM

    Machine Learning with Python

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Classification Algorithms, Feature Engineering

    4.7
    Rating, 4.7 out of 5 stars
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    18K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
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    IBM

    Machine Learning Introduction for Everyone

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning, Supervised Learning, Applied Machine Learning, Data Science, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

    4.6
    Rating, 4.6 out of 5 stars
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    305 reviews

    Beginner · Course · 1 - 4 Weeks

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    The University of Sydney

    Introduction to Linear Algebra

    Skills you'll gain: Linear Algebra, Markov Model, Geometry, Arithmetic, Algebra, General Mathematics, Advanced Mathematics, Probability, Mathematics and Mathematical Modeling, Mathematical Theory & Analysis, Mathematical Modeling, Applied Mathematics, Statistical Methods, Vector Databases, Engineering Analysis, Computational Logic

    4.8
    Rating, 4.8 out of 5 stars
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    40 reviews

    Intermediate · Course · 1 - 4 Weeks

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    Johns Hopkins University

    Linear Algebra: Linear Systems and Matrix Equations

    Skills you'll gain: Linear Algebra, Algebra, Advanced Mathematics, Mathematical Modeling, Engineering Analysis, Applied Mathematics, Mathematical Theory & Analysis, Geometry

    4.7
    Rating, 4.7 out of 5 stars
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    168 reviews

    Beginner · Course · 1 - 4 Weeks

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    Packt

    Machine Learning Foundations

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Dimensionality Reduction, Data Preprocessing, Python Programming, Recurrent Neural Networks (RNNs), Reinforcement Learning

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    New York University

    Machine Learning and Reinforcement Learning in Finance

    Skills you'll gain: Supervised Learning, Model Evaluation, Reinforcement Learning, Applied Machine Learning, Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Artificial Neural Networks, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Derivatives, Scikit Learn (Machine Learning Library), Markov Model, Regression Analysis, Deep Learning, Market Liquidity, Tensorflow

    3.7
    Rating, 3.7 out of 5 stars
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    820 reviews

    Intermediate · Specialization · 3 - 6 Months

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    O.P. Jindal Global University

    Machine Learning

    Skills you'll gain: Model Evaluation, Supervised Learning, Scikit Learn (Machine Learning Library), Tensorflow, Applied Machine Learning, Artificial Neural Networks, Python Programming, NumPy, Matplotlib, Deep Learning, Image Analysis, Machine Learning, Embeddings, Pandas (Python Package), Convolutional Neural Networks, Natural Language Processing, Regression Analysis

    Build toward a degree

    3.8
    Rating, 3.8 out of 5 stars
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    8 reviews

    Beginner · Course · 1 - 3 Months

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    University of London

    Machine Learning for All

    Skills you'll gain: Data Preprocessing, Machine Learning, Artificial Intelligence, Model Evaluation, Data Analysis, Image Analysis, Data Collection, Classification Algorithms

    Build toward a degree

    4.7
    Rating, 4.7 out of 5 stars
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    3.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Johns Hopkins University

    Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors

    Skills you'll gain: Linear Algebra, Applied Mathematics, Algebra, Advanced Mathematics, Geometry, Data Transformation, Applied Machine Learning, Dimensionality Reduction, Markov Model, Probability

    4.8
    Rating, 4.8 out of 5 stars
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    76 reviews

    Mixed · Course · 1 - 3 Months

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

  • Foundations of Machine Learning: Coursera
  • ML Concepts, Models & Workflow Essentials: Coursera
  • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI
  • Machine Learning with Python: IBM
  • Machine Learning Introduction for Everyone: IBM
  • Introduction to Linear Algebra: The University of Sydney
  • Linear Algebra: Linear Systems and Matrix Equations: Johns Hopkins University
  • Machine Learning Foundations: Packt
  • Machine Learning and Reinforcement Learning in Finance: New York University
  • Machine Learning: O.P. Jindal Global University

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