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  • Mathematics For Machine Learning

Mathematics for Machine Learning Courses

Mathematics for machine learning courses can help you learn linear algebra, calculus, probability, and statistics. You can build skills in optimization techniques, data analysis, and algorithm development. Many courses introduce tools like Python libraries such as NumPy and SciPy, that support implementing mathematical concepts in AI applications. You'll also explore key topics like regression analysis, dimensionality reduction, and neural networks, all of which are crucial for developing effective machine learning models.

Popular Mathematics for Machine Learning Courses and Certifications


  • Status: Free Trial
    Free Trial
    D

    Dartmouth College

    Foundations for Machine Learning

    Skills you'll gain: Probability & Statistics, Statistical Methods, Classification Algorithms, Calculus

    Build toward a degree

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Glasgow

    Machine Learning and its Applications

    Skills you'll gain: Model Training, Model Evaluation, Data Preprocessing, Machine Learning Methods, Statistical Methods, Machine Learning Software, Statistical Machine Learning, Data Validation, Data Processing, Data Quality, Mathematical Software, Classification Algorithms, Machine Learning Algorithms

    4.9
    Rating, 4.9 out of 5 stars
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    50 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    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
    Status: AI skills
    AI skills
    U

    University of Pennsylvania

    AI and Machine Learning Essentials with Python

    Skills you'll gain: Statistical Machine Learning, Data Preprocessing, Model Evaluation, PyTorch (Machine Learning Library), Statistical Methods, Probability, Probability & Statistics, Sampling (Statistics), Logistic Regression, Deep Learning, Probability Distribution, Python Programming, Statistical Modeling, Supervised Learning, Machine Learning, Agentic systems, Artificial Intelligence, Model Optimization, Algorithms, AI literacy

    4.5
    Rating, 4.5 out of 5 stars
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    57 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: New
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    J

    John Wiley & Sons

    Machine Learning For Dummies

    Skills you'll gain: Data Literacy, Model Evaluation, Scikit Learn (Machine Learning Library), Keras (Neural Network Library), Responsible AI, Data Ethics, Machine Learning Algorithms, Machine Learning Methods, Machine Learning, Model Training, Applied Machine Learning, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), AI Personalization, Deep Learning, Convolutional Neural Networks, Machine Learning Software, Python Programming, Data Preprocessing, Feature Engineering

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    G

    Google

    The Nuts and Bolts of Machine Learning

    Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Statistical Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Model Training, Random Forest Algorithm, Model Optimization, Predictive Modeling, Model Evaluation, Python Programming, Performance Tuning, Classification Algorithms

    4.8
    Rating, 4.8 out of 5 stars
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    640 reviews

    Advanced · Course · 1 - 3 Months

  • Status: New
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    Status: Preview
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    B

    Birla Institute of Technology & Science, Pilani

    Introduction to Machine Learning

    Skills you'll gain: Supervised Learning, Applied Machine Learning, Feature Engineering, Machine Learning Methods, Machine Learning Algorithms, Statistical Machine Learning, Predictive Modeling, Model Training, Model Evaluation, Scikit Learn (Machine Learning Library), Machine Learning, Regression Analysis, Bayesian Statistics, Artificial Intelligence and Machine Learning (AI/ML), Logistic Regression, Classification Algorithms, Decision Tree Learning, Model Optimization, Data Preprocessing, Probability & Statistics

    Build toward a degree

    Intermediate · 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
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    W

    Whizlabs

    NVIDIA: Fundamentals of Machine Learning

    Skills you'll gain: Data Preprocessing, Unsupervised Learning, Model Evaluation, Time Series Analysis and Forecasting, Supervised Learning, Machine Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning Algorithms, Data Processing, Model Training, Feature Engineering, Artificial Intelligence, Deep Learning, Classification Algorithms, Model Optimization, Regression Analysis

    4.4
    Rating, 4.4 out of 5 stars
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    30 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
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    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
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    3.8K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: New
    New
    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: 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

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

  • Foundations for Machine Learning: Dartmouth College
  • Machine Learning and its Applications: University of Glasgow
  • Statistics You Need to Know for Machine Learning: SAS
  • AI and Machine Learning Essentials with Python: University of Pennsylvania
  • Machine Learning For Dummies: John Wiley & Sons
  • The Nuts and Bolts of Machine Learning: Google
  • Introduction to Machine Learning: Birla Institute of Technology & Science, Pilani
  • Machine Learning Introduction for Everyone: IBM
  • NVIDIA: Fundamentals of Machine Learning: Whizlabs
  • Introduction to Machine Learning: Duke University

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