Josh Innovations

R Programming

By: Professor

R is an open source programming language. It is basically used for statistical analysis. It is also an alternative for all the expensive commercial statistic tool or software. It has a lot of packages and libraries. These libraries contain the more powerful function which can be implemented for own use. It also hawerful graphical functionality. It has a large part of the statistical community. Code written in R Programming is visible to the user, hence any user can do minor changes if it requires. It helps in the building of interactive course. It offers a good platform for data analytics. Enroll today and attend R Programming Online Training course demo by our real time expert.

Course Content

R Programming

  • Introduction to R
  • Business Analytics
  • Analytics concepts
  • The importance of R in analytics
  • R Language community and eco-system
  • Usage of R in industry
  • Installing R and other packages
  • Perform basic R operations using command line
  • Usage of IDE R Studio and various GUI
  • The datatypes in R and its uses
  • Built-in functions in R
  • Subsetting methods
  • Summarize data using functions
  • Use of functions like head(), tail(), for inspecting data
  • Use-cases for problem solving using R
  • Various phases of Data Cleaning
  • Functions used in Inspection
  • Data Cleaning Techniques
  • Uses of functions involved
  • Use-cases for Data Cleaning using R
  • Import data from spreadsheets and text files into R
  • Importing data from statistical formats
  • Packages installation for database import
  • Connecting to RDBMS from R using ODBC and basic SQL queries in R
  • Web Scraping
  • Other concepts on Data Import Techniques
  • What is EDA?
  • Why do we need EDA?
  • Goals of EDA
  • Types of EDA
  • Implementing of EDA
  • Boxplots, cor() in R
  • EDA functions
  • Multiple packages in R for data analysis
  • Some fancy plots
  • Use-cases for EDA using R
  • Story telling with Data
  • Principle tenets
  • Elements of Data Visualization
  • Infographics vs Data Visualization
  • Data Visualization & Graphical functions in R
  • Plotting Graphs
  • Customizing Graphical Parameters to improvise the plots
  • Various GUIs
  • Spatial Analysis
  • Other Visualization concepts


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