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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.


More to explore:

Popular Supervised Learning Courses and Certifications


  • E

    EDUCBA

    Python: Logistic Regression & Supervised ML

    Skills you'll gain: Model Evaluation, Feature Engineering, Supervised Learning, Exploratory Data Analysis, Classification Algorithms, Machine Learning Algorithms, Applied Machine Learning, Machine Learning Methods, Decision Tree Learning, Logistic Regression, Predictive Modeling, Data Analysis, Statistical Machine Learning, Scikit Learn (Machine Learning Library), Classification And Regression Tree (CART), Data Mining, Data Preprocessing, Pandas (Python Package), NumPy

    4.4
    Rating, 4.4 out of 5 stars
    ·
    17 reviews

    Mixed · Course · 1 - 4 Weeks

  • A

    Alberta Machine Intelligence Institute

    Introduction to Applied Machine Learning

    Skills you'll gain: Data Preprocessing, Data Ethics, Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Product Lifecycle Management, Case Studies, Data Collection, Supervised Learning, Business Requirements, Data Quality, Business Analysis, Unsupervised Learning, Artificial Intelligence

    4.7
    Rating, 4.7 out of 5 stars
    ·
    747 reviews

    Intermediate · Course · 1 - 4 Weeks

  • I

    IBM

    Deep Learning and Reinforcement Learning

    Skills you'll gain: Autoencoders, Recurrent Neural Networks (RNNs), Convolutional Neural Networks, Reinforcement Learning, Generative Adversarial Networks (GANs), Deep Learning, Unsupervised Learning, Machine Learning Methods, Transfer Learning, Artificial Neural Networks, Keras (Neural Network Library), Machine Learning, Artificial Intelligence, Computer Vision, Dimensionality Reduction, Model Evaluation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    291 reviews

    Intermediate · Course · 1 - 3 Months

  • 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
    ·
    3.3K reviews

    Mixed · Course · 1 - 4 Weeks

  • 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

  • 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

  • S

    Simplilearn

    AI ML with Deep Learning and Supervised Models

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Recurrent Neural Networks (RNNs), Model Deployment, Reinforcement Learning, Artificial Intelligence, Classification Algorithms, Classification And Regression Tree (CART), Tensorflow, Machine Learning Algorithms, Keras (Neural Network Library), Artificial Neural Networks, Deep Learning, Machine Learning, Decision Tree Learning, Predictive Analytics, Regression Analysis

    4
    Rating, 4 out of 5 stars
    ·
    10 reviews

    Beginner · Specialization · 1 - 3 Months

  • 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

  • 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
    ·
    2.5K reviews

    Mixed · Course · 1 - 3 Months

  • L

    LearnQuest

    Machine Learning Models in Science

    Skills you'll gain: Data Preprocessing, Applied Machine Learning, Dimensionality Reduction, Data Cleansing, Scikit Learn (Machine Learning Library), Data Transformation, Artificial Neural Networks, Random Forest Algorithm, Machine Learning, Unsupervised Learning, Supervised Learning, Classification Algorithms, Predictive Modeling, Python Programming

    4.1
    Rating, 4.1 out of 5 stars
    ·
    14 reviews

    Intermediate · Course · 1 - 4 Weeks

  • N

    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

  • S

    SAS

    Machine Learning Using SAS Viya

    Skills you'll gain: Data Preprocessing, Model Deployment, Model Evaluation, Supervised Learning, Decision Tree Learning, Applied Machine Learning, Predictive Modeling, Random Forest Algorithm, Feature Engineering, SAS (Software), Machine Learning, Data Analysis, Business Analysis, Artificial Neural Networks, Classification Algorithms, No-Code Development, Statistical Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    102 reviews

    Intermediate · Course · 1 - 3 Months

1…567…594

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

  • Python: Logistic Regression & Supervised ML: EDUCBA
  • Introduction to Applied Machine Learning: Alberta Machine Intelligence Institute
  • Deep Learning and Reinforcement Learning: IBM
  • Practical Machine Learning: Johns Hopkins University
  • Machine Learning with Small Data Part 1: Northeastern University
  • Introduction to Machine Learning in Sports Analytics: University of Michigan
  • AI ML with Deep Learning and Supervised Models: Simplilearn
  • Machine Learning for Engineers: Algorithms and Applications: Northeastern University
  • Machine Learning With Big Data: University of California San Diego
  • Machine Learning Models in Science: LearnQuest

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