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  • Supervised Learning

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.


Popular Supervised Learning Courses and Certifications


  • Status: New
    New
    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, Machine Learning Algorithms, Feature Engineering, Dimensionality Reduction, Machine Learning, Predictive Modeling, Predictive Analytics, Scikit Learn (Machine Learning Library), Classification Algorithms, Forecasting, Decision Tree Learning, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling

    4.6
    Rating, 4.6 out of 5 stars
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    10 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Preview
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    N

    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
    Free Trial
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    Google Cloud

    Introduction to AI and Machine Learning on Google Cloud

    Skills you'll gain: Generative AI, Google Cloud Platform, MLOps (Machine Learning Operations), Prompt Engineering, Tensorflow, AI Workflows, Cloud Infrastructure, Artificial Intelligence, Big Data, Model Deployment, Machine Learning, Supervised Learning

    4.6
    Rating, 4.6 out of 5 stars
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    310 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
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    J

    Johns Hopkins University

    Practical Machine Learning

    Skills you'll gain: Model Evaluation, Predictive Modeling, Machine Learning Algorithms, Statistical Machine Learning, Feature Engineering, Supervised Learning, Predictive Analytics, Applied Machine Learning, Data Preprocessing, R Programming, Classification Algorithms, Machine Learning, Random Forest Algorithm, Regression Analysis, Exploratory Data Analysis, Data Wrangling

    4.5
    Rating, 4.5 out of 5 stars
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    3.3K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    Machine Learning with Apache Spark

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

    4.5
    Rating, 4.5 out of 5 stars
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    113 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    D

    DeepLearning.AI

    Advanced Learning Algorithms

    Skills you'll gain: Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Artificial Neural Networks, Logistic Regression, Performance Tuning

    4.9
    Rating, 4.9 out of 5 stars
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    8.5K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    T

    The University of Chicago

    Machine Learning: Concepts and Applications

    Skills you'll gain: Keras (Neural Network Library), Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Classification Algorithms, Supervised Learning, Regression Analysis, Random Forest Algorithm, Dimensionality Reduction, Model Evaluation, Data Preprocessing, Statistical Methods, Tensorflow, Feature Engineering, Pandas (Python Package)

    3.9
    Rating, 3.9 out of 5 stars
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    25 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    N

    Northeastern University

    Machine Learning with Small Data Part 1

    Skills you'll gain: Transfer Learning, Small Data, Deep Learning, Applied Machine Learning, PyTorch (Machine Learning Library), Data Preprocessing, Unsupervised Learning, Machine Learning, Generative AI, Data Synthesis, Supervised Learning, Model Evaluation

    Mixed · Course · 1 - 3 Months

  • Status: New
    New
    P

    Packt

    Machine Learning for Absolute Beginners - Level 1

    Skills you'll gain: Generative AI, Responsible AI, Large Language Modeling, Data Ethics, Machine Learning, Applied Machine Learning, Artificial Intelligence, Supervised Learning, Predictive Modeling, Artificial Neural Networks, Unsupervised Learning, Deep Learning, Reinforcement Learning

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    Status: Free Trial
    Free Trial
    C

    Coursera

    Improve Accuracy with ML Ensemble Methods

    Skills you'll gain: Random Forest Algorithm, Decision Tree Learning, Data Preprocessing, Applied Machine Learning, Jupyter, Classification Algorithms, Java, Sampling (Statistics), Feature Engineering, Model Evaluation, Supervised Learning, Predictive Modeling, Machine Learning, Learning Styles, Program Evaluation, Program Implementation

    Intermediate · 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
    ·
    27 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    M

    Microsoft

    Microsoft Azure Machine Learning for Data Scientists

    Skills you'll gain: Responsible AI, Microsoft Azure, Unsupervised Learning, Databricks, MLOps (Machine Learning Operations), Applied Machine Learning, Classification Algorithms, Regression Analysis, Scikit Learn (Machine Learning Library), Predictive Modeling, Model Deployment, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Model Evaluation, Supervised Learning, Virtual Machines, Data Pipelines

    4.3
    Rating, 4.3 out of 5 stars
    ·
    177 reviews

    Intermediate · Course · 1 - 4 Weeks

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

  • Foundations of Machine Learning: Coursera
  • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
  • Introduction to AI and Machine Learning on Google Cloud: Google Cloud
  • Practical Machine Learning: Johns Hopkins University
  • Machine Learning with Apache Spark: IBM
  • Advanced Learning Algorithms: DeepLearning.AI
  • Machine Learning: Concepts and Applications: The University of Chicago
  • Machine Learning with Small Data Part 1: Northeastern University
  • Machine Learning for Absolute Beginners - Level 1: Packt
  • Improve Accuracy with ML Ensemble Methods: Coursera

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