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Supervised Learning Courses

Supervised learning courses can help you learn regression analysis, classification techniques, and model evaluation methods. You can build skills in feature selection, hyperparameter tuning, and understanding bias-variance tradeoff. Many courses introduce tools like Python libraries such as scikit-learn and TensorFlow, that support implementing algorithms and analyzing data.


More to explore:

Popular Supervised Learning Courses and Certifications


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    Northeastern University

    Statistical Learning for Engineering Part 1

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Machine Learning Software, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Logistic Regression, Unstructured Data, Model Evaluation, Dimensionality Reduction

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
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    U

    University of California San Diego

    Machine Learning With Big Data

    Skills you'll gain: Model Evaluation, Exploratory Data Analysis, Apache Spark, Classification Algorithms, Big Data, Regression Analysis, Data Mining, Applied Machine Learning, Data Preprocessing, Statistical Analysis, Machine Learning, Data Analysis, Unsupervised Learning, Predictive Modeling, Supervised Learning

    4.6
    Rating, 4.6 out of 5 stars
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    2.5K reviews

    Mixed · Course · 1 - 3 Months

  • Status: New
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    E

    EDUCBA

    Machine Learning with Python & Statistics

    Skills you'll gain: Sampling (Statistics), Data Mining, Statistical Hypothesis Testing, Probability, Linear Algebra, Statistical Analysis, Statistical Inference, Data Analysis, Probability Distribution, Statistics, Machine Learning Algorithms, Machine Learning, Python Programming

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
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    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 Access, Anomaly Detection, Statistical Analysis, Data Analysis, Data Cleansing, Data Manipulation, Machine Learning, Probability & Statistics, Jupyter, Data Import/Export, Pandas (Python Package), Data Transformation, Data Quality

    4.6
    Rating, 4.6 out of 5 stars
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    2.5K reviews

    Intermediate · Course · 1 - 3 Months

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    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 Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Generative Adversarial Networks (GANs), Machine Learning Methods, Deep Learning, Transfer Learning, Applied Machine Learning, Pandas (Python Package), Scikit Learn (Machine Learning Library), Python Programming, Machine Learning, Artificial Neural Networks, Data Processing, Natural Language Processing, Feature Engineering

    Intermediate · Course · 3 - 6 Months

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    Northeastern University

    Machine Learning for Engineers: Algorithms and Applications

    Skills you'll gain: Model Evaluation, Supervised Learning, Statistical Machine Learning, Machine Learning Algorithms, Unsupervised Learning, PyTorch (Machine Learning Library), Applied Machine Learning, Statistical Methods, Statistical Modeling, Machine Learning, Machine Learning Software, Statistical Analysis, Artificial Intelligence and Machine Learning (AI/ML), Regression Analysis, Classification Algorithms, Algorithms, Predictive Modeling, Dimensionality Reduction, Complex Problem Solving

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
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    U

    University of Washington

    Machine Learning: Classification

    Skills you'll gain: Classification Algorithms, Applied Machine Learning, Logistic Regression, Supervised Learning, Predictive Modeling, Decision Tree Learning, Data Preprocessing, Model Evaluation, Text Mining, Machine Learning Algorithms, Scalability, Machine Learning, Natural Language Processing, Big Data, Probability & Statistics, Algorithms

    4.7
    Rating, 4.7 out of 5 stars
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    3.7K reviews

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
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    U

    University of Colorado Boulder

    Supervised Text Classification for Marketing Analytics

    Skills you'll gain: Supervised Learning, Deep Learning, Scikit Learn (Machine Learning Library), Machine Learning, Tensorflow, Transfer Learning, Text Mining, Model Evaluation, Predictive Modeling, Data Manipulation, Marketing Analytics, Python Programming, Feature Engineering, Google Cloud Platform, Classification Algorithms, Artificial Neural Networks, Performance Metric

    Build toward a degree

    3.1
    Rating, 3.1 out of 5 stars
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    14 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    S

    Stanford University

    Fundamentals of Machine Learning for Healthcare

    Skills you'll gain: Healthcare Ethics, Data Ethics, Applied Machine Learning, Machine Learning Algorithms, Machine Learning, Responsible AI, Artificial Neural Networks, Healthcare Industry Knowledge, Model Evaluation, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Deep Learning, Convolutional Neural Networks, Health Policy, Data Preprocessing

    4.8
    Rating, 4.8 out of 5 stars
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    616 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    J

    Johns Hopkins University

    Mastering Neural Networks and Model Regularization

    Skills you'll gain: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Supervised Learning, Artificial Neural Networks, Model Evaluation, Decision Tree Learning, Network Planning And Design, Machine Learning, Computer Vision

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Machine Learning, Visual Recognition and NLP

    Skills you'll gain: Model Evaluation, Tensorflow, Supervised Learning, Artificial Neural Networks, Regression Analysis, Machine Learning Methods, Applied Machine Learning, Machine Learning Algorithms, Deep Learning, Image Analysis, Machine Learning, Random Forest Algorithm, Artificial Intelligence and Machine Learning (AI/ML), Decision Tree Learning, Natural Language Processing, Scikit Learn (Machine Learning Library), Convolutional Neural Networks, Computer Vision, Data Science, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
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    90 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Introduction to Machine Learning in Sports Analytics

    Skills you'll gain: Scikit Learn (Machine Learning Library), Supervised Learning, Applied Machine Learning, Model Evaluation, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Analytics, Decision Tree Learning, Machine Learning, Logistic Regression, Data Analysis, Classification Algorithms, Data Preprocessing, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
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    27 reviews

    Intermediate · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular supervised learning courses

  • Statistical Learning for Engineering Part 1: Northeastern University
  • Machine Learning With Big Data: University of California San Diego
  • Machine Learning with Python & Statistics: EDUCBA
  • Exploratory Data Analysis for Machine Learning: IBM
  • Machine Learning with PyTorch and Scikit-Learn: Packt
  • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
  • Machine Learning: Classification: University of Washington
  • Supervised Text Classification for Marketing Analytics: University of Colorado Boulder
  • Fundamentals of Machine Learning for Healthcare: Stanford University
  • Mastering Neural Networks and Model Regularization: Johns Hopkins University

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