## Supervised Learning with scikit-learn

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

Skip to main content## technology

## topic

## FAQs

Learn# Data science courses

Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.

- Learn at your own pace
- Get hands-on experience
- Complete bite-sized chapters

72 results ## Supervised Learning with scikit-learn

## Understanding Machine Learning

## Unsupervised Learning in Python

## Introduction to Deep Learning in Python

## Machine Learning with Tree-Based Models in Python

## Introduction to Natural Language Processing in Python

## Linear Classifiers in Python

## MLOps Concepts

## Machine Learning with scikit-learn

## Deep Learning with PyTorch

## AI Fundamentals

## Machine Learning for Time Series Data in Python

## Supervised Learning in R: Classification

## Preprocessing for Machine Learning in Python

## Introduction to TensorFlow in Python

## Introduction to Deep Learning with Keras

## Cluster Analysis in Python

## Feature Engineering for Machine Learning in Python

## Machine Learning for Business

## Image Processing in Python

## Extreme Gradient Boosting with XGBoost

## Dimensionality Reduction in Python

## Unsupervised Learning in R

## Image Processing with Keras in Python

## Sentiment Analysis in Python

## Model Validation in Python

## Advanced Deep Learning with Keras

## Hyperparameter Tuning in Python

## Feature Engineering for NLP in Python

## MLOps Deployment and Life Cycling

## Supervised Learning in R: Regression

## Modeling with tidymodels in R

## Building Chatbots in Python

## ARIMA Models in Python

## Supply Chain Analytics in Python

## Cluster Analysis in R

## Fraud Detection in Python

## Machine Learning with caret in R

## Winning a Kaggle Competition in Python

## Machine Learning with PySpark

## Machine Learning for Finance in Python

## Advanced NLP with spaCy

## Customer Segmentation in Python

## Introduction to Predictive Analytics in Python

## Building Recommendation Engines in Python

## Machine Learning in the Tidyverse

## Market Basket Analysis in Python

## Designing Machine Learning Workflows in Python

## Support Vector Machines in R

## Machine Learning for Marketing in Python

## Recurrent Neural Networks (RNN) for Language Modeling in Python

## Ensemble Methods in Python

## Machine Learning with Tree-Based Models in R

## Practicing Machine Learning Interview Questions in Python

## MLOps for Business

## Building Recommendation Engines with PySpark

## Introduction to Natural Language Processing in R

## Hyperparameter Tuning in R

## Text Mining with Bag-of-Words in R

## Introduction to Deep Learning with PyTorch

## Machine Learning for Marketing Analytics in R

## Introduction to Feature Engineering in R

## Sentiment Analysis in R

## Dimensionality Reduction in R

## Fully Automated MLOps

## Data Privacy and Anonymization in Python

## HR Analytics: Predicting Employee Churn in Python

## Machine Translation in Python

## Advanced Dimensionality Reduction in R

## Fraud Detection in R

## Predicting CTR with Machine Learning in Python

## Intermediate Predictive Analytics in Python

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

4 hoursMachine LearningGeorge Boormancourses

An introduction to machine learning with no coding involved.

2 hoursMachine LearningHadrien Lacroixcourses

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hoursMachine LearningBenjamin Wilsoncourses

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

4 hoursMachine LearningDan Beckercourses

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hoursMachine LearningElie Kawerkcourses

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

4 hoursMachine LearningKatharine Jarmulcourses

In this course you will learn the details of linear classifiers like logistic regression and SVM.

4 hoursMachine LearningMike Gelbartcourses

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

2 hoursMachine LearningFolkert Stijnmancourses

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

4 hoursMachine LearningHugo Bowne-Andersoncourses

Learn to create deep learning models with the PyTorch library.

4 hoursMachine LearningIsmail Elezicourses

Learn the fundamentals of AI. No programming experience required!

4 hoursMachine LearningNemanja Radojkovićcourses

This course focuses on feature engineering and machine learning for time series data.

4 hoursMachine LearningChris Holdgrafcourses

In this course you will learn the basics of machine learning for classification.

4 hoursMachine LearningBrett Lantzcourses

In this course you'll learn how to get your cleaned data ready for modeling.

4 hoursMachine LearningJames Chapmancourses

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

4 hoursMachine LearningIsaiah Hullcourses

Learn to start developing deep learning models with Keras.

4 hoursMachine LearningMiguel Estebancourses

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hoursMachine LearningShaumik Daityaricourses

Create new features to improve the performance of your Machine Learning models.

4 hoursMachine LearningRobert O'Callaghancourses

Understand the fundamentals of Machine Learning and how it's applied in the business world.

2 hoursMachine LearningKarolis Urbonascourses

Learn to process, transform, and manipulate images at your will.

4 hoursMachine LearningRebeca Gonzalezcourses

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

4 hoursMachine LearningSergey Fogelsoncourses

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

4 hoursMachine LearningJeroen Boeyecourses

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

4 hoursMachine LearningHank Roarkcourses

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

4 hoursMachine LearningAriel Rokemcourses

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

4 hoursMachine LearningVioleta Mishevacourses

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

4 hoursMachine LearningKasey Jonescourses

Build multiple-input and multiple-output deep learning models using Keras.

4 hoursMachine LearningZachary Deane-Mayercourses

Learn to tune hyperparameters in Python.

4 hoursMachine LearningAlex Scrivencourses

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

4 hoursMachine LearningRounak Banikcourses

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

4 hoursMachine LearningNemanja Radojkovićcourses

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

4 hoursMachine LearningJohn Mountcourses

Learn to streamline your machine learning workflows with tidymodels.

4 hoursMachine LearningDavid Svancercourses

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

4 hoursMachine LearningAlan Nicholcourses

Learn about ARIMA models in Python and become an expert in time series analysis.

4 hoursMachine LearningJames Fultoncourses

Leverage the power of Python and PuLP to optimize supply chains.

4 hoursMachine LearningAaren Stubberfieldcourses

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

4 hoursMachine LearningDmitriy Gorenshteyncourses

Learn how to detect fraud using Python.

4 hoursMachine LearningCharlotte Wergercourses

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

4 hoursMachine LearningZachary Deane-Mayercourses

Learn how to approach and win competitions on Kaggle.

4 hoursMachine LearningYauhen Babakhincourses

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

4 hoursMachine LearningAndrew Colliercourses

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

4 hoursMachine LearningNathan Georgecourses

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

5 hoursMachine LearningInes Montanicourses

Learn how to segment customers in Python.

4 hoursMachine LearningKarolis Urbonascourses

In this course you'll learn to use and present logistic regression models for making predictions.

4 hoursMachine LearningNele Verbiestcourses

Learn to build recommendation engines in Python using machine learning techniques.

4 hoursMachine LearningRobert O'Callaghancourses

Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.

5 hoursMachine LearningDmitriy Gorenshteyncourses

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

4 hoursMachine LearningIsaiah Hullcourses

Learn to build pipelines that stand the test of time.

4 hoursMachine LearningChristoforos Anagnostopouloscourses

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

4 hoursMachine LearningKailash Awaticourses

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

4 hoursMachine LearningKarolis Urbonascourses

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

4 hoursMachine LearningDavid Cecchinicourses

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

4 hoursMachine LearningRomán de las Herascourses

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

4 hoursMachine LearningSandro Raabecourses

Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.

4 hoursMachine LearningLisa Stuartcourses

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

3 hoursMachine LearningArne Warnkecourses

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

4 hoursMachine LearningJamen Longcourses

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

4 hoursMachine LearningKasey Jonescourses

Learn how to tune your model's hyperparameters to get the best predictive results.

4 hoursMachine LearningShirin Elsinghorst (formerly Glander)courses

Learn the bag of words technique for text mining with R.

4 hoursMachine LearningTed Kwartlercourses

Learn the power of deep learning in PyTorch. Build your first neural network, adjust hyperparameters, and tackle classification and regression problems.

4 hoursMachine LearningMaham Khancourses

In this course you'll learn how to use data science for several common marketing tasks.

4 hoursMachine LearningVerena Pfliegercourses

Learn a variety of feature engineering techniques to develop meaningful features that will uncover useful insights about your machine learning models.

4 hoursMachine LearningJose Hernandezcourses

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

4 hoursMachine LearningTed Kwartlercourses

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

4 hoursMachine LearningMatt Pickardcourses

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

4 hoursMachine LearningArturo Opsetmoen Amadorcourses

Learn to process sensitive information with privacy-preserving techniques.

4 hoursMachine LearningRebeca Gonzalezcourses

In this course you'll learn how to apply machine learning in the HR domain.

4 hoursMachine LearningHrant Davtyancourses

Are you curious about the inner workings of the models that are behind products like Google Translate?

4 hoursMachine LearningThushan Ganegedaracourses

Learn how to apply advanced dimensionality techniques such as t-SNE and GLRM.

4 hoursMachine LearningFederico Castanedocourses

Learn to detect fraud with analytics in R.

4 hoursMachine LearningBart Baesenscourses

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

4 hoursMachine LearningKevin Huocourses

Learn how to prepare and organize your data for predictive analytics.

4 hoursMachine LearningNele Verbiestcourses