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

Data Scientist and contributor to the Keras and TensorFlow deep learning libraries

Learn to train and assess models performing common machine learning tasks such as classification, regression and clustering.

Data Science Instructor at DataCamp

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

Core developer and co-maintainer of scikit-learn; Lecturer at Columbia University

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

Senior Data Scientist, Boeing

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

Data Scientist at Data Robot and co-author of caret

Learn how to build a model to automatically classify items in a school budget.

Co-founder of DrivenData

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

Director of Research at lateral.io

Learn how to visualize time series visualization in R, then practice with a stock-picking case study.

Quantitative trader and creator of thertrader.com

Learn to visualize multivariate datasets using lattice plotting.

Professor at the Indian Statistical Institute, a member of R-Core, and the creator of lattice.

Learn how to make predictions about the future using time series forecasting in R.

Professor of Statistics at Monash University