Advanced courses in DATA SCIENCE

Intermediate and advanced online courses in machine learning. Learn best practices for machine learning and AI software engineering from experienced professionals.

Our courses

Our Online Courses

feature engineering for machine learning course logo

Feature Engineering for Machine Learning

Learn to transform, combine, extract and create features to use in machine learning models.

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feature selection for machine learning course logo

Feature Selection for Machine Learning

Learn to select the best variables to make simpler, yet robust and reliable machine learning models.

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hyperparameter optimization for machine learning course logo

Hyperparameter Tuning for Machine Learning

Learn to tune hyperparameters and improve the performance of your machine learning models.

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machine learning with imbalanced data course logo

Machine Learning with Imbalanced Data

Learn about re-sampling, ensemble and cost-sensitive learning and how to create synthetic data.

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deployment of machine learning models course logo

Deployment of Machine Learning Models

Learn the best practices and tools to deploy machine learning models and reduce deployment time.

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testing and monitoring machine learning model deployments course logo

Testing and Monitoring Model Deployments

Learn to test and monitor machine learning model deployments, including shadow mode.

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Our Python Open-Source

Feature-engine open source Python library logo

Feature-engine

Check it out
  • feature engineering classes and functions

    Feature engineering and creation

    Tools and classes for missing data imputation, categorical encoding, outlier trimming, discretization, feature creation and more.

  • feature selection techniques and tools

    Feature selection methods

    A variety of methods to select the most relevant features in your data. Gathered from data science competitions and data mining articles.

  • feature engineering tutorials and demos

    Extensive docs and demos

    Discover the power of Feature-engine through its extensive documentation, tutorials, user guides and demos.

Our Book

  • code recipes for feature creation, extraction and transformation

    70+ feature engineering recipes

    Learn how to create, extract and transform features from tabular data, time series and text.

  • code implementations in open-source Python libraries

    Open-source code implementations

    Off-the-shelf feature engineering techniques with Scikit-learn, Feature-engine, Featuretools and more.

  • code implementations in open-source Python libraries

    Work with different data sources

    Extract, transform and create features from tabular, time series and text data.

Our Instructors

Soledad Galli Photo

Soledad Galli, PhD

Lead Data Scientist

Chris Samiullah Photo

Chris Samiullah

Senior Software Developer