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
IBM
Python for Data Science, AI & Development
Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis
4.6
Rating, 4.6 out of 5 stars
42K reviews
Beginner · Course · 1 - 3 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
Status: New
Status: Free Trial
Meta
Meta Full-Stack Developer
Skills you'll gain: Jest (JavaScript Testing Framework), Django (Web Framework), Version Control, Restful API, Responsive Web Design, Unix Commands, HTML and CSS, Git (Version Control System), GitHub, Relational Databases, Object Oriented Programming (OOP), Database Management Systems, Bootstrap (Front-End Framework), React.js, Mobile Development, SQL, Database Design, API Design, Linux Commands, Python Programming
4.7
Rating, 4.7 out of 5 stars
24K reviews
Beginner · Specialization · 3 - 6 Months
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
50 reviews
Beginner · Course · 1 - 4 Weeks
Status: Free Trial
University of Michigan
Applied Data Science with Python
Skills you'll gain: Matplotlib, Network Analysis, Feature Engineering, Data Visualization, Data Visualization Software, Interactive Data Visualization, Scientific Visualization, Pandas (Python Package), Applied Machine Learning, Supervised Learning, Text Mining, Visualization (Computer Graphics), Statistical Visualization, Network Model, Jupyter, NumPy, Graph Theory, Natural Language Processing, Python Programming, Data Processing
4.5
Rating, 4.5 out of 5 stars
34K reviews
Intermediate · Specialization · 3 - 6 Months

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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: 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
Status: Free Trial
Status: AI skills
IBM
IBM Data Science
Skills you'll gain: Dashboard, Data Visualization Software, Data Visualization, SQL, Predictive Modeling, Unsupervised Learning, Plotly, Interactive Data Visualization, Supervised Learning, Exploratory Data Analysis, Feature Engineering, Jupyter, Data Wrangling, Data Literacy, Data Analysis, Data Mining, Matplotlib, Generative AI, Professional Networking, Data Import/Export
Build toward a degree
4.6
Rating, 4.6 out of 5 stars
145K reviews
Beginner · Professional Certificate · 3 - 6 Months
Status: Free Trial
Multiple educators
Machine Learning
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 Algorithms, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), Artificial Intelligence, NumPy, Predictive Modeling, Deep Learning, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming
Build toward a degree
4.9
Rating, 4.9 out of 5 stars
35K reviews
Beginner · Specialization · 1 - 3 Months
Status: Free Trial
Google
Crash Course on Python
Skills you'll gain: Programming Principles, Python Programming, Computer Programming, Computational Thinking, Algorithms, Problem Management, Data Structures, Integrated Development Environments, Debugging, Development Environment
4.8
Rating, 4.8 out of 5 stars
39K reviews
Beginner · Course · 1 - 3 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
29K reviews
Beginner · Course · 1 - 4 Weeks