Manipulate, visualize, and perform statistical tests on HR data.

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Analyze text data in R using the tidy framework.

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

Learn how to analyze huge datasets using Apache Spark and R using the sparklyr package.

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

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

This course is designed to get you up to speed with the most important and powerful methodologies in statistics.

Learn to use the Bioconductor package limma for differential gene expression analysis.

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in Python.

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

Analyze spatial data using the sf and raster packages.

This course teaches you the skills and knowledge necessary to create and manage your own PostgreSQL databases.

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.