In this follow-up course, you will expand your stat modeling skills from the introduction and dive into more advanced concepts.

Predict employee turnover and design retention strategies.

Learn to automate many common file system tasks and be able to manage and communicate with processes.

Learn how to fit topic models using the Latent Dirichlet Allocation algorithm.

Learn to detect fraud with analytics in R.

Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

Master time series data using data.table in R.

Learn to create animated graphics and linked views entirely in R with plotly.

Learn all about how DataCamp builds the best platform to learn and teach data skills.

Learn to process sensitive information with privacy-preserving techniques.

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.