Objective: R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical ( linear & non-linear, classical statistical tests, time-series analysis , classification, clustering etc.)and graphical technique and is highly extensible . R is the best way to create reproducible high quality analysis .It has all the flexibility and power when dealing with data. Many data analysts and research programmers use R because R is the most prevalent language. Hence R is used as a fundamental tool for finance. Many quantitative analysts use R as their programming tool. Hence R helps in data importing and cleaning, depending on what manner of strategy you are using on. R is best for data science because it gives a broad variety of statistics. In addition, R provides the environment for statistical computing and design.

R Language

  • Live Demonstration
  •  Internship/Career Opportunities from Ignite and its associates.
  •  Hands on Practice Sessions
  •  24*7 Email Supports through Email.
  • Overview
  • History of R
  • Advantages and disadvantages
  • Downloading and installing
  • Introduction to R
  • Using the R Studio
  • R-Environment Setup
  • R-Data Types
  • R-Operator
  • R-Control Statement
  • R-Function
  • R-Strings
  • R-Vector
  • R-Lists
  • R-Matrices
  • R-Array
  • R-Factors
  • R-Data Frames
  • R-Data Reshaping
  • R-Databases
  • R- Charts
  • R-Regression
  • R-Decision Tree