What is scikit-learn?

Scikit-learn—or skilearn—is a very useful library of algorithms in Python for machine learning. It started out as a Google summer of code project in 2007 then was further developed by a group of data scientists from the French Institute for Research in Computer Science and Automation (FIRCA) and released to the public in 2010. The scikit-learn library lives at a github.com URL and is now a community effort that anyone with qualified skills can contribute to. While the library is primarily written in Python, it's also built on Python-based libraries that include NumPy, Matplotlib, pandas, and SciPy. It gives users tools for statistical modeling and machine learning, such as classification, clustering, regression, model selection, preprocessing, and dimensionality reduction.

What career opportunities can arise from learning scikit-learn?

When you learn scikit-learn, you put yourself in a position to be able to contribute to and help maintain the scikit-learn library. Top contributors include data scientists, software developers, machine learning researchers, research scientists, and open-source developers. Outside of contributing to the library, individuals in these career fields and others related to machine learning are better equipped to perform their job duties when they've learned how to utilize the algorithms in scikit-learn.

What skills or experience do I need to already have, before starting to learn scikit-learn?

Before starting to learn scikit-learn, you should have experience in and a sound understanding of Python. It is also often required to have experience in additional Python libraries, including NumPy, Scipy, Joblib, Matplotlib, and pandas.

How can taking online courses on Coursera help me learn scikit-learn?

Taking online courses on Coursera can help you learn about Python and machine learning as well as the specifics of using and creating algorithms for scikit-learn. You might learn how to build univariate and multivariate linear regression models using scikit-learn, use pandas to manage data, and perform exploratory data analysis and data visualization with seaborn, a Python library based on Matplotlib. With Coursera's online courses, you may also have the opportunity to make predictions in specific topics like electricity consumption, sentiment analysis, and career longevity for NBA rookies, for example.

What are the benefits of taking an online Scikit Learn course?

Online Scikit Learn courses offer a convenient and flexible way to enhance your knowledge or learn new Scikit Learn skills. Choose from a wide range of Scikit Learn courses offered by top universities and industry leaders tailored to various skill levels.

What Scikit Learn courses are best for training and upskilling employees or the workforce?

When looking to enhance your workforce's skills in Scikit Learn, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here .

Best Scikit-learn Courses & Certificates [2025]

Explore the Scikit-learn Course Catalog

Coursera Project Network
Scikit-Learn For Machine Learning Classification Problems
Skills you'll gain: Scikit Learn (Machine Learning Library), Applied Machine Learning, Machine Learning Algorithms, Classification And Regression Tree (CART), Supervised Learning, Random Forest Algorithm, Machine Learning, Unsupervised Learning, Data Analysis
4.5
Rating, 4.5 out of 5 stars
17 reviews
Beginner · Guided Project · Less Than 2 Hours
Status: Free Trial
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, NumPy, Data Analysis, Data Processing, Python Programming, Regression Analysis, Predictive Modeling, Machine Learning, Classification And Regression Tree (CART), Data Science, Statistical Hypothesis Testing, Statistical Methods, Computer Programming, Data Structures
3.7
Rating, 3.7 out of 5 stars
52 reviews
Beginner · Course · 1 - 4 Weeks
Status: New
Status: Free Trial
Coursera
Machine Learning with Scikit-learn, PyTorch & Hugging Face
Skills you'll gain: Generative AI, Supervised Learning, Unsupervised Learning, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, Applied Machine Learning, Machine Learning Algorithms, Data Collection, Data Cleansing, OpenAI, Feature Engineering, Data Ethics, Dimensionality Reduction, MLOps (Machine Learning Operations), Machine Learning, ChatGPT, Network Model, Network Architecture, Performance Tuning
Intermediate · Professional Certificate · 3 - 6 Months
Status: Free Trial
IBM
Machine Learning with Python
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
4.7
Rating, 4.7 out of 5 stars
18K reviews
Intermediate · Course · 1 - 3 Months
Coursera Project Network
Scikit-Learn to Solve Regression Machine Learning Problems
Skills you'll gain: Scikit Learn (Machine Learning Library), Predictive Modeling, Regression Analysis, Machine Learning Algorithms, Applied Machine Learning, Predictive Analytics, Python Programming, Machine Learning, Data Analysis, Random Forest Algorithm
4.8
Rating, 4.8 out of 5 stars
8 reviews
Beginner · Guided Project · Less Than 2 Hours
Status: Free Trial
IBM
Data Analysis with Python
Skills you'll gain: Exploratory Data Analysis, Data Wrangling, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Regression Analysis, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Feature Engineering, Data Visualization, Data Pipelines, NumPy, Python Programming
4.7
Rating, 4.7 out of 5 stars
19K reviews
Intermediate · Course · 1 - 3 Months

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Change my career

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Explore topics outside of work

Status: Free Trial
University of Michigan
Applied Machine Learning in Python
Skills you'll gain: Feature Engineering, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning, Decision Tree Learning, Unsupervised Learning, Python Programming, Dimensionality Reduction, Random Forest Algorithm, Regression Analysis
4.6
Rating, 4.6 out of 5 stars
8.6K reviews
Intermediate · Course · 1 - 4 Weeks
Status: New
Status: Free Trial
Packt
Mastering Machine Learning Algorithms using Python
Skills you'll gain: Data Science, Unsupervised Learning, Data Analysis, Machine Learning Algorithms, Predictive Modeling, Probability & Statistics, Applied Machine Learning, Exploratory Data Analysis, Classification And Regression Tree (CART), Python Programming, Random Forest Algorithm, Dimensionality Reduction, Regression Analysis, NumPy, Statistical Analysis, Data Processing, Pandas (Python Package), Deep Learning, Data Visualization, Data Manipulation
Intermediate · Specialization · 3 - 6 Months
Status: Free Trial
DeepLearning.AI
Supervised Machine Learning: Regression and Classification
Skills you'll gain: Supervised 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, Unsupervised Learning, Statistical Modeling
4.9
Rating, 4.9 out of 5 stars
30K reviews
Beginner · Course · 1 - 4 Weeks
Status: New
Packt
Data Science Foundations: NumPy, Pandas & Visualization
Skills you'll gain: Statistical Visualization, Scatter Plots, Pivot Tables And Charts, Histogram, Data Science, Computer Programming
Beginner · Course · 1 - 3 Months
Status: New
Status: Free Trial
University of Michigan
Applied Unsupervised Learning in Python
Skills you'll gain: Unsupervised Learning, Anomaly Detection, Supervised Learning, Python Programming, Exploratory Data Analysis
Advanced · Course · 1 - 4 Weeks
Coursera Project Network
Machine Learning Pipelines with Azure ML Studio
Skills you'll gain: Applied Machine Learning, Classification And Regression Tree (CART), Predictive Modeling, Microsoft Azure, Machine Learning, Supervised Learning, Feature Engineering, Data Pipelines, Data Science, Data Analysis, Data Processing, Data Cleansing, Application Deployment
4.5
Rating, 4.5 out of 5 stars
810 reviews
Beginner · Guided Project · Less Than 2 Hours