R Programming

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R programming certification training covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.

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Course Curriculum

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Any person who is interested in building a career in Data Science can opt for this course as a starting step.

There are no prerequisites for this course. Any person can join this course.

CH -01 An Introduction to R

·         History of S and R

·         Introduction to R

·         The R environment

·         What is Statistical Programming?

·         Why use a command line?

·         Your first R session

 

CH -02-Introduction to the R language

·         Starting and quitting R

·         Recording your work

·         Basic features of R

·         Calculating with R

·         Named storage

·         Functions

·         Exact or approximate?

·         R is case-sensitive

·         Listing the objects in the workspace

·         Vectors

·         Extracting elements from vectors

·         Vector arithmetic

·         Simple patterned vectors

·         Missing values and other special values

·         Character vectors

·         Factors

·         More on extracting elements from vectors

·         Matrices and arrays

·         Data frames

·         Dates and times

·         Built-in functions and online help

·         Built-in examples

·         Finding help when you don’t know the function name

·         Built-in graphics functions

·         Additional elementary built-in functions

·         Logical vectors and relational operators

·         Boolean Algebra

·         Logical Operations in R

·         Data Input & Output

·         Changing Directives

·         Dump() & Source()

·         Redirecting R Output

·         Saving & retrieving Image Files

·         Data Frames and the Read.table functions

 

CH -03 Programming statistical graphics  

  • High-level plots
  • Bar charts and dot charts
  • Pie charts
  • Histograms
  • Box plots
  • Scatterplots
  • QQ plots
  • Choosing a high-level graphic
  • Low-level graphics functions
  • The plotting region and margins
  • Adding to plots
  • Setting graphical parameters

 

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