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  • Math For Machine Learning

Math For Machine Learning Courses

Courses in Math for Machine Learning can help you learn linear algebra, calculus, probability, and statistics. You can build skills in data analysis, model evaluation, and algorithm optimization. Many courses introduce tools like Python libraries such as NumPy and SciPy, that support implementing mathematical concepts in AI and artificial intelligence projects. You'll also explore techniques like gradient descent and matrix factorization, which are crucial for developing effective machine learning models.

Popular Math For Machine Learning Courses and Certifications


  • Status: Free Trial
    Free Trial
    C

    Corporate Finance Institute

    Data Prep for Machine Learning in Python

    Skills you'll gain: Data Preprocessing, Feature Engineering, Data Import/Export, Exploratory Data Analysis, Data Cleansing, Statistical Visualization, Data Literacy, Data Visualization, Data Transformation, Data Analysis, Box Plots, Model Training, Python Programming, Data Science

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    Stanford University

    Fundamentals of Machine Learning for Healthcare

    Skills you'll gain: Machine Learning Methods, Healthcare Ethics, Data Ethics, Statistical Machine Learning, Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Responsible AI, Artificial Neural Networks, Healthcare Industry Knowledge, Model Evaluation, Medical Science and Research, Model Training, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Supervised Learning, Health Informatics, Generative Model Architectures, Deep Learning, Health Policy

    4.8
    Rating, 4.8 out of 5 stars
    ·
    635 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning with R: Build, Analyze & Predict

    Skills you'll gain: Data Analysis, Machine Learning Algorithms, Statistical Analysis, Probability & Statistics, Probability Distribution, R Programming, Machine Learning Methods, Statistical Methods, R (Software), Applied Machine Learning, Statistical Machine Learning, Statistics, Statistical Modeling, Machine Learning, Statistical Inference, Classification Algorithms, Statistical Programming, Correlation Analysis, Data Manipulation, Supervised Learning

    4.6
    Rating, 4.6 out of 5 stars
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    16 reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Octave for Machine Learning: Analyze & Visualize

    Skills you'll gain: Plot (Graphics), Scientific Visualization, Text Mining, Statistical Analysis, Statistical Methods, Data Visualization, Visualization (Computer Graphics), Descriptive Statistics, Unstructured Data, Data Analysis, Statistical Software, Computer Programming, Mathematical Software, Data Transformation, Data Preprocessing, Data Manipulation, Analytics, Data Processing, Machine Learning, Operations

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    N

    New York Institute of Finance

    Using Machine Learning in Trading and Finance

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Financial Trading, Data Pipelines, Machine Learning Methods, Applied Machine Learning, Technical Analysis, Machine Learning, Securities Trading, Statistical Machine Learning, Model Training, Market Trend, Market Data, Data Preprocessing, Deep Learning, Python Programming, Feature Engineering, Model Evaluation, Correlation Analysis, Artificial Neural Networks

    3.9
    Rating, 3.9 out of 5 stars
    ·
    379 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Pittsburgh

    Linear Algebra and Regression Fundamentals for Data Science

    Skills you'll gain: NumPy, Matplotlib, Plot (Graphics), Linear Algebra, Pandas (Python Package), Data Manipulation, Applied Mathematics, Data Visualization, Python Programming, Data Analysis, Data Science, Regression Analysis, Data Processing, Statistical Analysis, Mathematics and Mathematical Modeling, Numerical Analysis, Mathematical Modeling, Machine Learning, Computational Logic, Logical Reasoning

    Build toward a degree

    3.9
    Rating, 3.9 out of 5 stars
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    8 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Advanced Methods in Machine Learning Applications

    Skills you'll gain: Model Evaluation, Unsupervised Learning, Applied Machine Learning, Dimensionality Reduction, Reinforcement Learning, Machine Learning Methods, Regression Analysis, Machine Learning, Data Mining, Machine Learning Algorithms, Predictive Modeling, Random Forest Algorithm, Decision Tree Learning, Model Optimization, Logistic Regression, Classification Algorithms

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Illinois Urbana-Champaign

    Machine Learning for Accounting with Python

    Skills you'll gain: Model Evaluation, Machine Learning Algorithms, Model Optimization, Scikit Learn (Machine Learning Library), Model Training, Unsupervised Learning, Text Mining, Time Series Analysis and Forecasting, Pandas (Python Package), Classification Algorithms, Machine Learning, Applied Machine Learning, Supervised Learning, Predictive Modeling, Unstructured Data, Feature Engineering, Jupyter, Regression Analysis, Data Preprocessing, Python Programming

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
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    45 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    U

    University of Minnesota

    Matrix Methods

    Skills you'll gain: Dimensionality Reduction, Linear Algebra, Unsupervised Learning, Machine Learning Methods, Numerical Analysis, Mathematical Modeling, Applied Mathematics, Applied Machine Learning, Data Manipulation, Algorithms, Python Programming

    4.1
    Rating, 4.1 out of 5 stars
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    249 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    S

    SAS

    Statistics You Need to Know for Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Logistic Regression, Correlation Analysis, Applied Machine Learning, Model Evaluation, Data Modeling

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    A

    Arizona State University

    Introduction to Machine Learning with Python

    Skills you'll gain: Supervised Learning, Unsupervised Learning, Generative Adversarial Networks (GANs), Generative AI, Model Training, Deep Learning, Image Analysis, Machine Learning Methods, Machine Learning Algorithms, Applied Machine Learning, Python Programming, Machine Learning, Generative Model Architectures, Artificial Neural Networks, Model Evaluation, Data Processing, Classification Algorithms, Computer Vision, Computer Programming, Regression Analysis

    3.6
    Rating, 3.6 out of 5 stars
    ·
    26 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    P

    Packt

    Machine Learning with PyTorch and Scikit-Learn

    Skills you'll gain: Reinforcement Learning, Dimensionality Reduction, PyTorch (Machine Learning Library), Machine Learning Algorithms, Data Preprocessing, Model Training, Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Deep Learning, Generative AI, Applied Machine Learning, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Model Optimization, Machine Learning, Artificial Neural Networks, Natural Language Processing, Feature Engineering

    Intermediate · Course · 3 - 6 Months

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

  • Data Prep for Machine Learning in Python: Corporate Finance Institute
  • Fundamentals of Machine Learning for Healthcare: Stanford University
  • Machine Learning with R: Build, Analyze & Predict: EDUCBA
  • Octave for Machine Learning: Analyze & Visualize: EDUCBA
  • Using Machine Learning in Trading and Finance: New York Institute of Finance
  • Linear Algebra and Regression Fundamentals for Data Science: University of Pittsburgh
  • Advanced Methods in Machine Learning Applications: Johns Hopkins University
  • Machine Learning for Accounting with Python: University of Illinois Urbana-Champaign
  • Matrix Methods: University of Minnesota
  • Statistics You Need to Know for Machine Learning: SAS

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