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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: New
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    Coursera

    Automate ML Pipelines for Peak Performance

    Skills you'll gain: MLOps (Machine Learning Operations), Feature Engineering, Model Optimization, Model Training, Workflow Management, Predictive Modeling

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Board Infinity

    Applied Machine Learning Systems with FastAPI for Developers

    Skills you'll gain: Feature Engineering, Model Deployment, Data Preprocessing, Machine Learning Methods, Scikit Learn (Machine Learning Library), Supervised Learning, Machine Learning Algorithms, Applied Machine Learning, Machine Learning, Test Script Development, Model Evaluation, Unsupervised Learning, Containerization, Data Processing, Data Wrangling, Unit Testing, Development Testing, Software Development, Python Programming, Application Programming Interface (API)

    Intermediate · Course · 1 - 4 Weeks

  • Status: New
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    Packt

    Data Science with Python

    Skills you'll gain: Plotly, PyTorch (Machine Learning Library), NumPy, Matplotlib, Pandas (Python Package), Plot (Graphics), Data Visualization Software, Interactive Data Visualization, Machine Learning Methods, Python Programming, Applied Machine Learning, Scatter Plots, Numerical Analysis, Data Manipulation, Deep Learning, Image Analysis, Linear Algebra, Data Wrangling

    Intermediate · Course · 1 - 3 Months

  • Status: New
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    LearnKartS

    Python for Data Science with AI

    Skills you'll gain: Matplotlib, Pandas (Python Package), Plot (Graphics), Data Visualization, Seaborn, Data Manipulation, Data Visualization Software, Pseudocode, Problem Solving, Data Analysis, Programming Principles, Data Processing, AI literacy, Dashboard, Python Programming, Data Science, Computer Programming, Generative AI

    Mixed · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
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    IBM

    IBM Generative AI Engineering

    Skills you'll gain: Prompt Engineering, Prompt Patterns, Data Wrangling, Large Language Modeling, LangChain, Retrieval-Augmented Generation, Exploratory Data Analysis, Unsupervised Learning, Generative Model Architectures, PyTorch (Machine Learning Library), ChatGPT, Generative AI, Restful API, Prompt Engineering Tools, LLM Application, Keras (Neural Network Library), Responsible AI, Vector Databases, Fine-tuning, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
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    99K reviews

    Beginner · Professional Certificate · 3 - 6 Months

  • Status: New
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    Packt

    Machine Learning with R

    Skills you'll gain: Model Evaluation, Classification Algorithms, R Programming, Apache Spark, Deep Learning, Applied Machine Learning, Data Wrangling, Keras (Neural Network Library), Unsupervised Learning, Model Training, Statistical Machine Learning, Data Manipulation, Machine Learning Methods, Machine Learning Algorithms, Data Science, Machine Learning, Tidyverse (R Package), Data Analysis, Bayesian Network, Logistic Regression

    Intermediate · Course · 3 - 6 Months

  • Status: Free Trial
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    LearnQuest

    AI for Scientific Research

    Skills you'll gain: Data Preprocessing, Feature Engineering, Model Evaluation, Bioinformatics, Exploratory Data Analysis, Random Forest Algorithm, Pandas (Python Package), Scikit Learn (Machine Learning Library), Applied Machine Learning, Data Manipulation, Data Processing, Dimensionality Reduction, Data Cleansing, Model Optimization, Keras (Neural Network Library), Machine Learning Algorithms, Data Transformation, Model Training, Machine Learning, Data Science

    3.3
    Rating, 3.3 out of 5 stars
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    102 reviews

    Beginner · Specialization · 3 - 6 Months

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    Edureka

    Getting Started with Automated Machine Learning (AutoML)

    Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Model Optimization, Automation, Artificial Intelligence and Machine Learning (AI/ML), Model Training, Machine Learning Methods, No-Code Development, Data Preprocessing, Scikit Learn (Machine Learning Library), Machine Learning, Model Evaluation, Applied Machine Learning, Predictive Modeling, Feature Engineering, Data-Driven Decision-Making, Machine Learning Algorithms, Artificial Intelligence, Data Validation, Data Quality

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Packt

    Python - Complete Python, Django, Data Science and ML Guide

    Skills you'll gain: Predictive Modeling, Data Preprocessing, Django (Web Framework), Data Visualization, Plot (Graphics), Predictive Analytics, Statistical Visualization, Model Training, Model Evaluation, File I/O, Application Programming Interface (API), Programming Principles, Databases, Development Environment, Web Applications, Code Reusability, Data Management, Functional Design, Memory Management, Data Validation

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
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    LearnQuest

    Introduction to Data Science and scikit-learn in Python

    Skills you'll gain: Feature Engineering, Exploratory Data Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data Manipulation, Applied Machine Learning, NumPy, Statistical Machine Learning, Classification Algorithms, Data Preprocessing, Data Processing, Data Wrangling, Python Programming, Regression Analysis, Predictive Modeling, Machine Learning Algorithms, Machine Learning, Model Evaluation, Data Science, Statistical Hypothesis Testing

    3.8
    Rating, 3.8 out of 5 stars
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    60 reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
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    Packt

    Mastering Machine Learning Algorithms using Python

    Skills you'll gain: Data Science, Unsupervised Learning, Exploratory Data Analysis, Probability & Statistics, Machine Learning Algorithms, Applied Machine Learning, Classification And Regression Tree (CART), Data Analysis, Python Programming, Random Forest Algorithm, Dimensionality Reduction, Predictive Modeling, NumPy, Regression Analysis, Statistical Analysis, Data Processing, Deep Learning, Pandas (Python Package), Data Visualization, Data Manipulation

    Intermediate · Specialization · 3 - 6 Months

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    The University of Chicago

    Machine Learning: Concepts and Applications

    Skills you'll gain: Keras (Neural Network Library), Machine Learning Methods, Unsupervised Learning, Machine Learning Algorithms, Deep Learning, Machine Learning, Statistical Machine Learning, Machine Learning Software, Decision Tree Learning, Applied Machine Learning, Scikit Learn (Machine Learning Library), Classification Algorithms, Supervised Learning, Regression Analysis, Artificial Intelligence and Machine Learning (AI/ML), Random Forest Algorithm, Model Training, Dimensionality Reduction, Model Evaluation, Data Preprocessing

    3.9
    Rating, 3.9 out of 5 stars
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    25 reviews

    Intermediate · Course · 1 - 3 Months

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

  • Automate ML Pipelines for Peak Performance: Coursera
  • Applied Machine Learning Systems with FastAPI for Developers: Board Infinity
  • Data Science with Python: Packt
  • Python for Data Science with AI: LearnKartS
  • IBM Generative AI Engineering: IBM
  • Machine Learning with R: Packt
  • AI for Scientific Research: LearnQuest
  • Getting Started with Automated Machine Learning (AutoML): Edureka
  • Python - Complete Python, Django, Data Science and ML Guide: Packt
  • Introduction to Data Science and scikit-learn in Python: LearnQuest

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