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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
    I

    IBM

    Exploratory Data Analysis for Machine Learning

    Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Statistical Methods, Data Preprocessing, Statistical Inference, Statistical Hypothesis Testing, Data Processing, Applied Machine Learning, Data Access, Statistics, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Data Science, Data Wrangling, Machine Learning, Probability & Statistics, Data Import/Export, Data Transformation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    2.6K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
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    IBM

    Machine Learning Capstone

    Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Applied Machine Learning, Predictive Modeling, Data Presentation, Machine Learning, Collaborative Software, Data Analysis, Predictive Analytics, Technical Communication, Machine Learning Algorithms, Statistical Analysis, Scikit Learn (Machine Learning Library), Keras (Neural Network Library), Descriptive Statistics, Regression Analysis, Python Programming, Text Mining, Artificial Neural Networks

    4.7
    Rating, 4.7 out of 5 stars
    ·
    216 reviews

    Advanced · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning: Regression

    Skills you'll gain: Regression Analysis, Model Evaluation, Predictive Modeling, Supervised Learning, Statistical Machine Learning, Statistical Modeling, Model Training, Applied Machine Learning, Machine Learning Algorithms, Machine Learning Methods, Feature Engineering, Machine Learning, Data Preprocessing, Model Optimization, Statistical Methods, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
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    5.6K reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    Unsupervised Machine Learning

    Skills you'll gain: Unsupervised Learning, Dimensionality Reduction, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Applied Machine Learning, Data Preprocessing, Text Mining, Machine Learning, Big Data, Model Evaluation, Performance Metric

    4.7
    Rating, 4.7 out of 5 stars
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    370 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Washington

    Machine Learning: Classification

    Skills you'll gain: Classification Algorithms, Classification And Regression Tree (CART), Applied Machine Learning, Model Training, Logistic Regression, Supervised Learning, Predictive Modeling, Decision Tree Learning, Data Preprocessing, Model Evaluation, Text Mining, Machine Learning Algorithms, Feature Engineering, Data Cleansing, Scalability, Model Optimization, Risking, Machine Learning, Natural Language Processing, Probability & Statistics

    4.7
    Rating, 4.7 out of 5 stars
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    3.7K reviews

    Mixed · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    B

    Board Infinity

    Machine Learning and Deep Learning for Software Engineers

    Skills you'll gain: Feature Engineering, Model Evaluation, Model Deployment, Fine-tuning, Data Preprocessing, Model Training, Deep Learning, Machine Learning Methods, Model Optimization, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Scalability, Hugging Face, Docker (Software), Supervised Learning, Machine Learning Algorithms, MLOps (Machine Learning Operations), Applied Machine Learning, Software Development, Machine Learning

    Intermediate · Specialization · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Alberta

    Fundamentals of Reinforcement Learning

    Skills you'll gain: Reinforcement Learning, Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Agentic systems, Markov Model, Decision Intelligence, Algorithms

    4.8
    Rating, 4.8 out of 5 stars
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    2.9K reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Advanced Learning Algorithms

    Skills you'll gain: Model Training, Machine Learning Algorithms, Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Responsible AI, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Model Optimization, Fine-tuning, Artificial Neural Networks, Logistic Regression

    4.9
    Rating, 4.9 out of 5 stars
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    8.8K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    Duke University

    Interpretable Machine Learning

    Skills you'll gain: Responsible AI, Large Language Modeling, Decision Tree Learning, Data Ethics, Regression Analysis, Artificial Intelligence, Machine Learning, Applied Machine Learning, Statistical Modeling, Python Programming, Embeddings, Deep Learning, Machine Learning Algorithms, Artificial Neural Networks

    4.6
    Rating, 4.6 out of 5 stars
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    30 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    C

    Coursera

    Deep Learning Engineering

    Skills you'll gain: Model Deployment, Fine-tuning, PyTorch (Machine Learning Library), Model Evaluation, Model Training, Vision Transformer (ViT), Model Optimization, Transfer Learning, MLOps (Machine Learning Operations), Natural Language Processing, Debugging, Containerization, Kubernetes, Docker (Software), Distributed Computing, Performance Tuning, Tensorflow, Deep Learning, Cloud Computing, Data Pipelines

    Advanced · Specialization · 1 - 3 Months

  • C

    Coursera

    Machine Learning for Kyphosis Disease Classification

    Skills you'll gain: Feature Engineering, Data Visualization Software, Data Cleansing, Classification And Regression Tree (CART), Random Forest Algorithm, Decision Tree Learning, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Data Wrangling, Data Preprocessing, Data Science, Model Training, Machine Learning, Machine Learning Algorithms, Python Programming

    4.6
    Rating, 4.6 out of 5 stars
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    13 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: New
    New
    Status: Preview
    Preview
    C

    Case Western Reserve University

    Mathematical Thinking for Advanced Mathematics

    Skills you'll gain: Computational Thinking, Mathematical Theory & Analysis, Mathematics and Mathematical Modeling, Advanced Mathematics, Mathematical Modeling, Logical Reasoning, Deductive Reasoning, Critical Thinking, Applied Mathematics, Theoretical Computer Science, General Mathematics, Problem Solving, Mathematics Education, Analytical Skills, Numerical Analysis, Algebra, Geometry, Quantitative Research, Estimation, Verification And Validation

    Intermediate · Course · 1 - 3 Months

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

  • Exploratory Data Analysis for Machine Learning: IBM
  • Machine Learning Capstone: IBM
  • Machine Learning: Regression: University of Washington
  • Unsupervised Machine Learning: IBM
  • Machine Learning: Classification: University of Washington
  • Machine Learning and Deep Learning for Software Engineers: Board Infinity
  • Fundamentals of Reinforcement Learning: University of Alberta
  • Advanced Learning Algorithms: DeepLearning.AI
  • Interpretable Machine Learning: Duke University
  • Deep Learning Engineering: Coursera

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