Course Outline

  • R's environment
  • Object oriented programming in R
  • S3
  • S4
  • Reference classes
  • Performance profiling
  • Exception handling
  • Debugging R code
  • Creating R packages
  • Unit testing
  • C/C++ coding in R
  • SEXPRs
  • Calling dynamically loaded libraries from R
  • Writing and compiling C/C++ code from R
  • Improving R's performance with C++ linear algebra library

Requirements

Linux Operating System

 7 Hours

Testimonials (3)

Related Courses

Introduction to Data Visualization with Tidyverse and R

7 Hours

Advanced R

7 Hours

Algorithmic Trading with Python and R

14 Hours

Anomaly Detection with Python and R

14 Hours

Programming with Big Data in R

21 Hours

R Fundamentals

21 Hours

Cluster Analysis with R and SAS

14 Hours

Data and Analytics - from the ground up

42 Hours

Data Analytics With R

21 Hours

Data Mining with R

14 Hours

Deep Learning for Finance (with R)

28 Hours

Deep Learning for Banking (with R)

28 Hours

Data Mining & Machine Learning with R

14 Hours

Foundation R

7 Hours

Forecasting with R

14 Hours

Related Categories

1