Use the advanced features of Julia to work with complex data
Reactive programming is shaping the future of how we model data. With reactive, not only can you concisely wrangle and analyze static data, you can effectively work with data as a real-time infinite feed. Reactive Extensions (Rx) first gained traction in 2009 and has been ported to over a dozen major languages and platforms.
Refine your data science skills with the heavy armory of tools provided by Julia
The R programming language has arguably become the single most important tool for computational statistics, visualization, and data science. With this Learning Path, master the basics that you'll need as a data scientist. You'll work your data like never before.
Unleash the powerful capabilities of R to work effectively with data.
Over 100 hands-on tasks to help you effectively solve real-world data problems using the most popular R packages and techniques