Supervised Learning

Supervised learning is a type of machine learning where an algorithm learns from labeled training data, and makes predictions based on that data. Coursera's supervised learning catalogue teaches you to construct predictive models, understand the principles of machine learning algorithms, and apply them to real-world problems. You'll learn about various supervised learning techniques such as linear regression, K-nearest neighbors, support vector machines and decision trees. Additionally, you'll gain insights into concepts like overfitting, underfitting, bias-variance tradeoffs, and cross-validation. This knowledge will be invaluable whether you're aiming to become a data scientist, machine learning engineer, or simply want to understand the technology driving today's artificial intelligence advancements.
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Explore the Supervised Learning Course Catalog

  • Status: Free Trial

    Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Predictive Modeling, Feature Engineering, Artificial Intelligence, Classification And Regression Tree (CART), Python Programming, Regression Analysis, Statistical Modeling, Data Transformation

  • Status: Free Trial

    Skills you'll gain: Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Decision Tree Learning, Scikit Learn (Machine Learning Library), Matplotlib, Random Forest Algorithm, Machine Learning, Predictive Modeling, Data Science, Python Programming, Classification And Regression Tree (CART), Mathematical Modeling, Applied Mathematics, Exploratory Data Analysis, Statistical Programming, Regression Analysis, Feature Engineering, Data Cleansing, Performance Tuning

  • Status: New
    Status: Free Trial

    Skills you'll gain: Generative AI, Supervised Learning, Generative Model Architectures, Unsupervised Learning, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Data Collection, Machine Learning Algorithms, OpenAI, Feature Engineering, Data Ethics, Dimensionality Reduction, MLOps (Machine Learning Operations), Machine Learning, Multimodal Prompts, Data Processing, Network Architecture

  • Status: New
    Status: Preview

    Skills you'll gain: PyTorch (Machine Learning Library), Deep Learning, Machine Learning, Supervised Learning, Generative AI, Feature Engineering, Scikit Learn (Machine Learning Library), Data Processing, Unsupervised Learning, Natural Language Processing, Artificial Neural Networks, Reinforcement Learning

  • Status: New
    Status: Preview

    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, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Unstructured Data, Probability & Statistics, Dimensionality Reduction, Algorithms

  • Status: New
    Status: Free Trial

    Skills you'll gain: Supervised Learning, Unsupervised Learning, 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), Forecasting, Data Processing, Anomaly Detection, Data Manipulation, Regression Analysis, Statistical Modeling, Data Transformation, Data Cleansing

What brings you to Coursera today?

  • Status: Free Trial

    Multiple educators

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Responsible AI, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming

  • Status: Free Trial

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Feature Engineering, Applied Machine Learning, Scikit Learn (Machine Learning Library), Machine Learning, Predictive Modeling, Dimensionality Reduction, Regression Analysis, Decision Tree Learning, Classification And Regression Tree (CART), Statistical Modeling

  • Status: Free Trial

    Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Regression Analysis, Dimensionality Reduction, Reinforcement Learning, Generative Model Architectures, Deep Learning, Data Analysis, Statistical Methods, Applied Machine Learning, Statistical Inference, Predictive Modeling, Statistical Hypothesis Testing, Data Processing, Machine Learning Algorithms, Machine Learning, Data Science, Python Programming

  • Status: Free Trial

    University of Washington

    Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms, Big Data

  • Status: Free Trial

    Johns Hopkins University

    Skills you'll gain: PyTorch (Machine Learning Library), Unsupervised Learning, Computer Vision, Machine Learning Algorithms, Applied Machine Learning, Image Analysis, Dimensionality Reduction, Supervised Learning, Reinforcement Learning, Feature Engineering, Regression Analysis, Data Cleansing, Machine Learning, Data Mining, Scikit Learn (Machine Learning Library), Statistical Machine Learning, Advanced Analytics, Deep Learning, Artificial Neural Networks, Decision Tree Learning

  • Status: Free Trial

    Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Regression Analysis, Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Predictive Modeling, Random Forest Algorithm, Bayesian Statistics

What brings you to Coursera today?

Leading partners

  • Packt
  • DeepLearning.AI
  • University of Colorado Boulder
  • IBM
  • EDUCBA
  • Google Cloud
  • University of Washington
  • Johns Hopkins University