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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


  • Status: Free Trial
    Free Trial
    I

    IBM

    IBM Introduction to Machine Learning

    Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Feature Engineering, Dimensionality Reduction, Supervised Learning, Classification Algorithms, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Statistical Methods, Data Preprocessing, Applied Machine Learning, Model Evaluation, Statistical Inference, Predictive Modeling, Machine Learning Methods, Statistical Hypothesis Testing, Model Training, Data Processing, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    3.4K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    J

    John Wiley & Sons

    Machine Learning: Real-World Applications

    Skills you'll gain: Model Evaluation, Keras (Neural Network Library), Data Ethics, Image Analysis, AI Personalization, Model Training, Convolutional Neural Networks, Model Optimization, Machine Learning, Applied Machine Learning, Feature Engineering, Machine Learning Methods, Computer Vision, Supervised Learning, Data Preprocessing, Program Evaluation, Unsupervised Learning, Python Programming, Data Science, Algorithms

    Intermediate · Course · 1 - 3 Months

  • Status: Top AI Program
    Top AI Program
    I

    IBM

    IBM Machine Learning

    Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Autoencoders, Feature Engineering, Dimensionality Reduction, Supervised Learning, Generative AI, Classification Algorithms, Regression Analysis, Time Series Analysis and Forecasting, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Generative Model Architectures, Scikit Learn (Machine Learning Library), Deep Learning, Data Science, Machine Learning, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    3.7K reviews

    Intermediate · Professional Certificate · 3 - 6 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    J

    John Wiley & Sons

    Core Machine Learning Algorithms and Model Validation

    Skills you'll gain: Model Evaluation, Scikit Learn (Machine Learning Library), Keras (Neural Network Library), Machine Learning Algorithms, Model Training, Applied Machine Learning, Deep Learning, Machine Learning Methods, Machine Learning Software, Statistical Modeling, Predictive Modeling, Supervised Learning, Machine Learning, Python Programming, Unsupervised Learning, Data Science, Predictive Analytics, Data Preprocessing, Algorithms, Data Analysis

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    E

    EDUCBA

    AI & Machine Learning: Apply, Build & Solve

    Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Artificial Intelligence, Agentic systems, Machine Learning Algorithms, Bayesian Network, Applied Machine Learning, Computational Logic, Machine Learning, Unsupervised Learning, Bayesian Statistics, Artificial Neural Networks, Reinforcement Learning, Markov Model, Algorithms, Programming Principles

    5
    Rating, 5 out of 5 stars
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    10 reviews

    Mixed · Course · 1 - 3 Months

  • Status: Preview
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    I

    IBM

    Machine Learning Introduction for Everyone

    Skills you'll gain: Model Evaluation, Predictive Modeling, Model Training, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

    4.5
    Rating, 4.5 out of 5 stars
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    316 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    C

    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, Model Training, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Machine Learning Software, Dimensionality Reduction, Machine Learning, Predictive Modeling, Data Wrangling, Predictive Analytics, Forecasting, Data Processing, Anomaly Detection

    4.2
    Rating, 4.2 out of 5 stars
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    17 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
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    U

    University of London

    Machine Learning for All

    Skills you'll gain: Model Training, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Feature Engineering, Machine Learning, Artificial Intelligence, Statistical Machine Learning, Model Evaluation, Data Literacy, Machine Learning Algorithms, AI literacy, Responsible AI, Data Collection

    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
    Free Trial
    J

    Johns Hopkins University

    Linear Algebra: Linear Systems and Matrix Equations

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

    4.7
    Rating, 4.7 out of 5 stars
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    179 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    D

    Duke University

    Introduction to Machine Learning

    Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Machine Learning Methods, Transfer Learning, Reinforcement Learning, Convolutional Neural Networks, Deep Learning, Image Analysis, Applied Machine Learning, Model Training, Natural Language Processing, Machine Learning, Model Optimization, Artificial Neural Networks, Supervised Learning, Unsupervised Learning, Python Programming, Computer Vision, Medical Imaging

    4.7
    Rating, 4.7 out of 5 stars
    ·
    3.8K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Machine Learning with Apache Spark

    Skills you'll gain: Apache Spark, Machine Learning, Generative AI, Model Evaluation, Supervised Learning, Apache Hadoop, Data Pipelines, Unsupervised Learning, Data Processing, Extract, Transform, Load, Predictive Modeling, Model Deployment, Classification Algorithms, Data Transformation, Regression Analysis

    4.5
    Rating, 4.5 out of 5 stars
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    115 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Octave for Machine Learning: Data Analysis Mastery

    Skills you'll gain: Plot (Graphics), Scripting, Scientific Visualization, Graphing, Data Visualization, Scripting Languages, Data Visualization Software, Scalability, Text Mining, Statistical Analysis, Time Series Analysis and Forecasting, Statistical Methods, Mathematical Software, File I/O, Software Installation, Numerical Analysis, Mathematical Modeling, Code Reusability, Python Programming, Data Analysis

    Beginner · Specialization · 1 - 3 Months

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

  • IBM Introduction to Machine Learning: IBM
  • Machine Learning: Real-World Applications: John Wiley & Sons
  • IBM Machine Learning: IBM
  • Core Machine Learning Algorithms and Model Validation: John Wiley & Sons
  • AI & Machine Learning: Apply, Build & Solve: EDUCBA
  • Machine Learning Introduction for Everyone: IBM
  • Foundations of Machine Learning: Coursera
  • Machine Learning for All: University of London
  • Linear Algebra: Linear Systems and Matrix Equations: Johns Hopkins University
  • Introduction to Machine Learning: Duke University

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