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

Explore data and build predictive models.

This course equips learners with practical data analysis and machine learning with pandas and other frameworks such as NumPy and TensorFlow.

This course equips learners with practical data analysis and machine learning with pandas and other frameworks such as NumPy and TensorFlow.

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

Dive into machine learning with Python. Learn to build models, preprocess data, and evaluate results using Python libraries like Scikit-learn, pandas, and numpy, to unlock powerful insights for a variety of business and data science applications.

Many problems are solved using Machine Learning. This course will teach you how to pick the ML algorithm that can help you create the right ML model to solve the problem at hand.

Master machine learning with R, a popular language for data analysis and statistical modeling. Learn how to apply machine learning algorithms, preprocess data, and evaluate models using R’s powerful libraries and tools for data science.

A comprehensive source to help you learn Machine learning with TensorFlow

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

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

Teach computers how to make decisions and play games with the Minimax Algorithm!