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R- Programming

R is an open source programming language and software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.Polls, surveys of data miners, and studies of scholarly literature databases show that R's popularity has increased substantially in recent years


    Aim of Course:   This course will provide a basic introduction to R, and its use in organizing and exploring data. The emphasis is on understanding and working with fundamental R data structures and we will introduce some basic R programming techniques. Once you've completed this course you'll be able to enter, save, retrieve, manipulate, and summarize data using R; you will also have the proper foundation to build your programming skills in R and take advantage of the full power of R.  

Course Program:


SESSION 1: Getting Started with R

  • What is statistical programming?
  • The R package
  • Installation of R
  • The R command line
  • Function calls, symbols, and assignment
  • Packages
  • Getting help on R
  • Basic features of R
  • Calculating with R
  SESSION 2: Matrices, Array, Lists, and Data Frames
  • Character vectors
  • Operations on the logical vectors
  • Creating the matrices and operations on it
  • Creating the array and operations on it
  • Creating the lists and operations on it
  • Making data frames
  • Working with data frames
  SESSION3: Getting Data in and out of R       SESSION4: Data Manipulation and Exploration:
  • Variable transformations
  • Creating Dummy variables
  • Data set options (Rename, Label)
  • Keep / Drop Columns
  • Identification and Dealing with the Missing data
  • Sorting the data
  • Handling the Duplicates
  • Joining and Merging (Inner,Left,Right and Cross Join)
  • Calculating Descriptive Statistics
  • Summarize numeric variables
  • Summarize factor variables
  • Transpose Data
  • Aggregated functions using Group by
  • dplyr anddatatable packages for the data manipulation
  • Data preparation using the sqldf package
  SESSION5: Conditional Statements and Loops:
  • If Else
  • Nested If Else
  • For Loop
  • While Loop
  SESSION6: Functions:   SESSION7: Graphical procedures
  • Pie chart
  • Bar Chart
  • Box plot
  • Scatter plot
  • Multi Scatter plot
  • Word cloud etc.…
   SESSION8: Advanced R and Real time analytics examples:
  • Data extraction from the Twitter
  • Text Data handling
  • Positive and Negative word cloud
  • Required packages for the analytics
  • Sentiment analysis using the real time example
  • R code automation
  • Time series analysis with the real time Telecom data
  • Couple of examples with the time series data
  SESSION9: Integration with R
  • Hadoop with R
  • Tableau with R


1.very experienced professional faculty. And Lab facility and project explanations are also very good . Its lovely professional e-learning portal to learn depth in concept and leaning each point in subject. So i suggest to my friends to join here. -SURESH GUPTHA -Hadoop developer

2.I have taken multiple trainings from Airis trainings over a period of 3yrs. The course contents are very good and to the point. The instructors are very knowledgeable.SUMAN SETTI Regular Student

3 ."It is an awesome experience with airis staff , very good instructors ." ROSLIN MIRIYAM Regular Student

4 .According to my point of view airis trainings is dynamic e-learning portal in india where all faculty came from Data science industry with sound knowledge. For freshers and experienced professionals also this institute is best source for getting job in IT industry PREETHI developer