The Complete R Programming for Data Science – 7 courses in 1

In The Complete R–Programming for Data Science & Statistics program, we have carefully designed 7 Full–Fledged courses into 1 Master Course of 200+ videos, 50+ R–Packages, Core Machine Learning and statistics concepts, 75+ practice problems and 2 Industrial projects

By end of this course, you will be able to solve Industry Data Science project in R starting including model building, model diagnostics and presenting actionable business insights

Here’s how you will progress across the 7 courses in the Master Course:

Getting started with R–programming: First, you will learn to write your own R code and perform basic programming tasks. You will begin with the base R programming course, where you will master the fundamental data structures such as vectors, lists, dataframes , understand the core programming constructs and get enough coding practice. You will also create full featured plots for data analysis using base graphics.

Advanced coding with Tidyverse: Then you will move to advanced coding in R based on the tidyverse using the dplyr package. You will start using the elegant pipe syntax provided by the magrittr package and the data manipulation verbs.

Data.table for data wrangling in R: Then You will move on to master the data.table package which has advanced capabilities for fast data manipulation. Data Scientists love this package for its incredible speed gains. Here, you will do fast data imports, create pivot tables and get comfortable with wrangling data. You will learn techniques to make your R code run super fast.