R

Analyze, communicate, and design your own sophisticated and interactive web applications using the R (v 3.4) Shiny (1.1.0) package

Build rich and collaborative applications using client-side code with React, Redux, and Firebase

Understand how machine learning works and get hands-on experience in using R to build algorithms that can solve several real-world problems.

Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications

Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more.

Solve real-world data problems with R and machine learning

Unleash the power of the Raspberry Pi 3 board to create interesting IoT projects

Build efficient forecasting models using traditional time series models and machine learning algorithms.

Discover how project Reactor enhances the reactive programming paradigm and allows you to build scalable asynchronous applications

A comprehensive guide in developing and deploying high performance microservices with Rust

Practical examples with real-world projects in GIS, Remote sensing, Geospatial data management and Analysis using the R programming language

Learn exploratory data analysis concepts using powerful R packages to enhance your R data analysis skills

Explore powerful R packages to create predictive models using ensemble methods

Learn how to write cross platform React Native code by using effective design patterns in the JavaScript world. Get to know industry standard patterns as well as situational patterns. Decouple your application with these set of 'Idea patterns'.

Design and implement professional level programs by exploring modern data structures and algorithms in Rust.