Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.

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!

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

Learn how to build a graphical dashboard with spreadsheets to track the performance of financial securities.

In this course you'll learn to add multiple variables to linear models and to use logistic regression for classification.

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

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

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

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

In this course, you'll learn the basics of relational databases and how to interact with them.

Leverage your Python and SQL knowledge to create a pipeline ingesting, transforming and loading data into a database.

Learn the basics of spreadsheets by working with rows, columns, addresses, and ranges.

Learn to perform linear and logistic regression with multiple explanatory variables.