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Scikit-Learn Courses

Scikit-learn courses can help you learn data preprocessing, model selection, classification techniques, and regression analysis. You can build skills in evaluating model performance, feature engineering, and implementing machine learning pipelines. Many courses introduce tools like Jupyter Notebooks and Python libraries, that support applying these skills in practical projects.


Popular Scikit-Learn Courses and Certifications


  • Status: Free Trial
    Free Trial
    C

    Coursera

    From Raw to Ready: Data Preparation in Python

    Skills you'll gain: Data Integration, Data Import/Export, NumPy, Data Wrangling, Data Manipulation, Data Preprocessing, Pandas (Python Package), Data Pipelines, Data Transformation, Data Processing, Data Access, Data Structures, Numerical Analysis

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Applied Unsupervised Learning in Python

    Skills you'll gain: Unsupervised Learning, Embeddings, Applied Machine Learning, Data Quality, Unstructured Data, Machine Learning Methods, Anomaly Detection, Supervised Learning, Data Preprocessing, Data Transformation, Python Programming, Exploratory Data Analysis

    4.8
    Rating, 4.8 out of 5 stars
    ·
    6 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    Illinois Tech

    Statistical Learning

    Skills you'll gain: Statistical Analysis, Data Analysis, Data Science, Statistical Programming, Statistical Methods, Statistical Machine Learning, Statistical Modeling, Applied Machine Learning, Model Evaluation, Regression Analysis, Statistics, Machine Learning Methods, Machine Learning Algorithms, Bayesian Statistics, Supervised Learning, Statistical Inference, Machine Learning, Unsupervised Learning, Predictive Modeling, Logistic Regression

    Build toward a degree

    4.6
    Rating, 4.6 out of 5 stars
    ·
    9 reviews

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    E

    EDUCBA

    Master Machine Learning with TensorFlow: Basics to Advanced

    Skills you'll gain: Data Preprocessing, Tensorflow, Scikit Learn (Machine Learning Library), Machine Learning, Applied Machine Learning, Feature Engineering, Deep Learning, Machine Learning Algorithms, Matplotlib, Jupyter, Python Programming, Data Wrangling, Data Processing, NumPy, Data Cleansing, Model Training, Data Manipulation, Data Transformation, Artificial Neural Networks, Seaborn

    Mixed · Course · 1 - 3 Months

  • 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, Machine Learning Methods, Predictive Analytics, Feature Engineering, Classification And Regression Tree (CART), Machine Learning Algorithms, Predictive Modeling, Machine Learning Software, Analytics, Decision Tree Learning, Machine Learning, Logistic Regression, Data Analysis, Data Analysis Software, Classification Algorithms, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    27 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Machine Learning in Python: Analyze & Apply

    Skills you'll gain: Matplotlib, Plot (Graphics), NumPy, Pandas (Python Package), Applied Machine Learning, Python Programming, Scikit Learn (Machine Learning Library), Data Visualization, Supervised Learning, Feature Engineering, Machine Learning, Natural Language Processing, Model Optimization, Machine Learning Algorithms, Text Mining, Data Manipulation, Predictive Modeling, Model Training, Unsupervised Learning, Data Management

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    Data Mining in Python

    Skills you'll gain: Data Mining, Unsupervised Learning, Data Science, Anomaly Detection, Data Manipulation, Machine Learning Methods, Statistical Methods, Linear Algebra, Python Programming, Classification Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    11 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    P

    Packt

    NumPy, Matplotlib & Pandas – Data Science Prerequisites

    Skills you'll gain: NumPy, Plot (Graphics), Pandas (Python Package), Scientific Visualization, Data Manipulation, Scatter Plots, Machine Learning Methods, Applied Machine Learning, Machine Learning, Data Science, Machine Learning Algorithms, Data Analysis Software, Statistical Methods, Histogram, Data Processing, Numerical Analysis, Data Import/Export, Probability Distribution, Linear Algebra, Classification Algorithms

    4.4
    Rating, 4.4 out of 5 stars
    ·
    8 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    AI with Python: Apply & Implement ML Models

    Skills you'll gain: Data Preprocessing, Dimensionality Reduction, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, PyTorch (Machine Learning Library), Deep Learning, Keras (Neural Network Library), Tensorflow, Artificial Intelligence, Data Cleansing, Model Evaluation, Jupyter, Python Programming, Machine Learning Methods, Applied Machine Learning, Artificial Neural Networks, Rmarkdown, Data Presentation, Machine Learning, Model Optimization

    4.6
    Rating, 4.6 out of 5 stars
    ·
    13 reviews

    Mixed · Course · 1 - 4 Weeks

  • P

    Packt

    Machine Learning: Random Forest with Python from Scratch©

    Skills you'll gain: Matplotlib, Random Forest Algorithm, Predictive Modeling, Predictive Analytics, Machine Learning Algorithms, Plot (Graphics), Data Visualization, Data Preprocessing, Machine Learning, Programming Principles, Data Manipulation, Data Cleansing, Data Transformation, Supervised Learning, Python Programming, Data Science, Model Training, Decision Tree Learning, NumPy, Pandas (Python Package)

    Beginner · Course · 1 - 3 Months

  • Status: New
    New
    P

    Packt

    Databricks ML in Action

    Skills you'll gain: Model Deployment, Databricks, MLOps (Machine Learning Operations), Feature Engineering, Apache Spark, Model Training, Data Preprocessing, Applied Machine Learning, Data Lakes, Extract, Transform, Load, AI Workflows, Hugging Face, Data Pipelines, PySpark, Vector Databases, Application Deployment, Artificial Intelligence and Machine Learning (AI/ML), Data Architecture, Machine Learning, Artificial Intelligence

    Intermediate · Course · 1 - 3 Months

  • Status: Preview
    Preview
    U

    University of Colorado Boulder

    Introduction to Python for Scientific Computing

    Skills you'll gain: Scientific Visualization, NumPy, Data Visualization, Debugging, Matplotlib, Numerical Analysis, Engineering Calculations, Mathematical Software, Code Reusability, Integrated Development Environments, Computational Thinking, Engineering Analysis, Programming Principles, Data Analysis, Computer Programming, Model Optimization

    4.8
    Rating, 4.8 out of 5 stars
    ·
    17 reviews

    Beginner · Course · 1 - 4 Weeks

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In summary, here are 10 of our most popular scikit-learn courses

  • From Raw to Ready: Data Preparation in Python: Coursera
  • Applied Unsupervised Learning in Python: University of Michigan
  • Statistical Learning: Illinois Tech
  • Master Machine Learning with TensorFlow: Basics to Advanced: EDUCBA
  • Introduction to Machine Learning in Sports Analytics: University of Michigan
  • Machine Learning in Python: Analyze & Apply: EDUCBA
  • Data Mining in Python: University of Michigan
  • NumPy, Matplotlib & Pandas – Data Science Prerequisites: Packt
  • AI with Python: Apply & Implement ML Models: EDUCBA
  • Machine Learning: Random Forest with Python from Scratch©: Packt

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