DATA ANALYTICS WITH R [Basic to Advance]

Summary (or descriptive) statistics are the first figures used to represent nearly every dataset. They also form the foundation for much more complicated computations and analyses. Thus, in spite of being composed of simple methods, they are essential to the analysis process. This tutorial will explore the ways in which R can be used to calculate summary statistics, including the mean, standard deviation, range, and percentiles. Also introduced is the summary function, which is one of the most useful tools in the R set of commands.
Master the use of the R interactive environment
Expand R by installing R packages
Explore and understand how to use the R documentation
Read Structured Data into R from various sources
Understand the different data types in R
Understand the different data structures in R
Understand how to use dates in R
Use R for mathematical operations
Use of vectorized calculations
Write user-defined R functions
Use control statements
Understand how to link data, statistical methods, and actionable questions
Write Loop constructs in R
Use Apply to iterate functions across data
Reshape data to support different analyses
Understand split-apply-combine (group-wise operations) in R
Deal with missing data
Manipulate strings in R
Understand basic regular expressions in R
Understand base R graphics
Be familiar with trellis (lattice) graphics
Write multivariate models in R
Generating plots (Generate plot in R, Graphs, Bar Plots, Line Plots, Histogram, components of Pie Chart.)
Regression in R