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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


  • C

    Coursera

    Logistic Regression with NumPy and Python

    Skills you'll gain: Matplotlib, Data Visualization, Seaborn, Logistic Regression, NumPy, Data Analysis, Jupyter, Data Science, Machine Learning, Machine Learning Algorithms, Python Programming, Supervised Learning, Classification Algorithms, Algorithms

    4.5
    Rating, 4.5 out of 5 stars
    ·
    396 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Feature Engineering and Bias Detection

    Skills you'll gain: Feature Engineering, Data Ethics, Unsupervised Learning, Dimensionality Reduction, Responsible AI, Text Mining, Data Preprocessing, Data Transformation, MLOps (Machine Learning Operations), Anomaly Detection, Exploratory Data Analysis, Machine Learning Methods, Machine Learning, Model Evaluation, Natural Language Processing, Data Science, Quality Assurance, Data Pipelines, Data Visualization, Python Programming

    4.4
    Rating, 4.4 out of 5 stars
    ·
    76 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Enterprise Model Deployment

    Skills you'll gain: Model Deployment, Apache Spark, Data Pipelines, MLOps (Machine Learning Operations), PySpark, IBM Cloud, Jupyter, Docker (Software), Machine Learning, Data Science, Python Programming, Scalability, Design Thinking

    4.3
    Rating, 4.3 out of 5 stars
    ·
    59 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Preview
    Preview
    K

    Korea Advanced Institute of Science and Technology(KAIST)

    Practical Python for AI Coding 2

    Skills you'll gain: Matplotlib, Data Visualization, Tensorflow, NumPy, Pandas (Python Package), Object Oriented Programming (OOP), Seaborn, Python Programming, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Data Manipulation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    26 reviews

    Beginner · 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
    ·
    90 reviews

    Advanced · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Data Analysis and Hypothesis Testing

    Skills you'll gain: Data Visualization, Exploratory Data Analysis, Data Presentation, Probability Distribution, Statistical Hypothesis Testing, Dashboard, Data Analysis, Data Science, Probability & Statistics, Statistical Analysis, Jupyter, Matplotlib, Data Preprocessing, Data Cleansing, Pandas (Python Package), Statistical Inference, Statistics, Data Manipulation, Python Programming, Machine Learning

    4.3
    Rating, 4.3 out of 5 stars
    ·
    127 reviews

    Advanced · Course · 1 - 4 Weeks

  • C

    Coursera

    Analyze Box Office Data with Seaborn and Python

    Skills you'll gain: Exploratory Data Analysis, Seaborn, Plotly, Data Visualization, Data Visualization Software, Interactive Data Visualization, Data Analysis, Python Programming, Predictive Modeling, Data Science, Jupyter, Cloud Applications

    4.5
    Rating, 4.5 out of 5 stars
    ·
    182 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • Status: Free Trial
    Free Trial
    I

    IBM

    AI Workflow: Business Priorities and Data Ingestion

    Skills you'll gain: Design Thinking, Data Science, Process Design, Strategic Thinking, Data Pipelines, Data Validation, Data Processing, Workflow Management, Data Cleansing, Data Quality, Business Priorities, NumPy, Machine Learning, Python Programming

    4.3
    Rating, 4.3 out of 5 stars
    ·
    188 reviews

    Intermediate · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of Michigan

    More Applied Data Science with Python

    Skills you'll gain: Unsupervised Learning, Data Mining, Social Network Analysis, ChatGPT, Embeddings, Bayesian Network, Machine Learning Methods, Data Science, Supervised Learning, Generative AI, Machine Learning, Anomaly Detection, Data Preprocessing, Data Analysis, Recurrent Neural Networks (RNNs), Data Manipulation, Python Programming, Exploratory Data Analysis, Machine Learning Algorithms, Classification Algorithms

    4.3
    Rating, 4.3 out of 5 stars
    ·
    8 reviews

    Advanced · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Applied Machine Learning: Techniques and Applications

    Skills you'll gain: Model Evaluation, Data Preprocessing, Computer Vision, Machine Learning Algorithms, Image Analysis, Supervised Learning, Applied Machine Learning, Feature Engineering, Classification Algorithms, Data Cleansing, Scikit Learn (Machine Learning Library), Data Transformation

    3.7
    Rating, 3.7 out of 5 stars
    ·
    12 reviews

    Intermediate · Course · 1 - 4 Weeks

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

    Coursera

    Advanced Machine Learning Techniques

    Skills you'll gain: Transfer Learning, Data Preprocessing, Hugging Face, Model Evaluation

    Intermediate · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    E

    EDUCBA

    Mastering Recommendation Systems with Python

    Skills you'll gain: Model Evaluation, Data Preprocessing, Feature Engineering, AI Personalization, Applied Machine Learning, Data Science, Machine Learning, Scalability, Data Manipulation, Python Programming, Data Transformation, Pandas (Python Package), Predictive Analytics, Machine Learning Methods, Predictive Modeling, Text Mining, Development Environment, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, NumPy

    4.7
    Rating, 4.7 out of 5 stars
    ·
    59 reviews

    Intermediate · Specialization · 1 - 3 Months

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

  • Logistic Regression with NumPy and Python: Coursera
  • AI Workflow: Feature Engineering and Bias Detection: IBM
  • AI Workflow: Enterprise Model Deployment: IBM
  • Practical Python for AI Coding 2: Korea Advanced Institute of Science and Technology(KAIST)
  • AI Workflow: Machine Learning, Visual Recognition and NLP: IBM
  • AI Workflow: Data Analysis and Hypothesis Testing: IBM
  • Analyze Box Office Data with Seaborn and Python: Coursera
  • AI Workflow: Business Priorities and Data Ingestion: IBM
  • More Applied Data Science with Python: University of Michigan
  • Applied Machine Learning: Techniques and Applications: Johns Hopkins University

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