R Programming

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Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.


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In R Programming, you will master the basics of this widely used open source language, including factors, lists, and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis. Oracle estimated over 2 million R users worldwide in 2012, cementing R as a leading programming language in statistics and data science. Every year, the number of R users grows by about 40%, and an increasing number of organizations are using it in their day-to-day activities. 

What you will learn

  • R source code and R functions,
  • R studio
  • R data types 
  • Command lines and command prompts 
  • Time-series analysis 
  • Linear regression and logistic regression 
  • Data frames 
  • R objects 
  • Basic data
  • CRAN and Fortran code 
  • Assignment operators
  • Read.table functions 
  • Normal distribution 
  • Generalized linear models 
  • Survival analysis


For Organization

R will just not help you in the technical fields, it will also be a great help in your business.

  • Here, the major reason is that R is open-source, therefore it can be modified and redistributed as per the user’s need. It is great for visualization and has far more capabilities as compared to other tools.
  • For data-driven businesses, lack of Data Scientists is a huge concern. Companies are using R programming as their core platform and are recruiting trained R programmers.   

For Individual 

R language is used extensively in Data Science. This field offers some of the highest-paying jobs in the world today. Data Scientists who are proficient in R make more than $117,000 on an average per year. If you want to enter the field of Data Science and earn a lucrative salary, then you must definitely learn R.

Course Content

What is R? 12:00 Play
Why R? 12:00 Play
Installing R 12:00 Play
R environment 12:00 Play
How to get help in R 12:00 Play
R Studio Overview 12:00 Play
Variables in R 10:00 Play
Scalars 10:00 Play
Vectors 10:00 Play
Matrices 10:00 Play
List 10:00 Play
Data frames 10:00 Play
Cbind,Rbind, attach and detach functions in R 10:00 Play
Factors 10:00 Play
Getting a subset of Data 10:00 Play
Missing values 10:00 Play
Converting between vector types 10:00 Play
Reading Tabular Data files Play
Reading CSV files 12:00 Play
Importing data from excel 12:00 Play
Loading and storing data with a clipboard 12:00 Play
Accessing database 12:00 Play
Saving in R data 12:00 Play
Loading R data objects 12:00 Play
Writing data to file 12:00 Play
Writing text and output from analyses to file 12:00 Play
Selecting rows/observations 11:00 Play
Rounding Number 11:00 Play
Creating string from a variable 11:00 Play
Search and Replace a String or Number 11:00 Play
Selecting columns/fields 11:00 Play
Merging data 11:00 Play
Relabeling the column names 11:00 Play
Data sorting 11:00 Play
Data aggregation 11:00 Play
Finding and removing duplicate records 11:00 Play
Apply Function Family 15:00 Play
Commonly used Mathematical Functions 15:00 Play
Commonly used Summary Functions 15:00 Play
Commonly used String Functions 15:00 Play
User-defined functions 15:00 Play
local and global variable 15:00 Play
Working with dates 15:00 Play
While loop 12:00 Play
If loop 12:00 Play
For loop 12:00 Play
Arithmetic operations 12:00 Play
Box plot 11:00 Play
Histogram 11:00 Play
Pie graph 11:00 Play
Line chart 11:00 Play
Scatterplot 11:00 Play
Developing graphs 11:00 Play
Cover all the current trending packages for Graphs 11:00 Play

Course Details

R is a widely used statistical programming language that’s beloved by people in academia and the tech industry. But that makes it sound more intimidating than it actually is. R is a great first language for anyone interested in answering questions with data analysis, data visualization, and data science.

Who Should Attend?

  • Those interested in the field of data science
  • Those who want to learn R programming from scratch
  • Those looking for a robust, structured learning program on R
  • Software or Data Engineers interested in learning R Programming


While there are no prerequisites, participants would benefit if they have elementary programming knowledge.

Course Info.

35 Hours
2-3 Hours/week
R Foundation
Video Script

Training Options

Selfpaced Training

  • Lifetime access to high-quality self-paced eLearning content curated by industry experts
  • 3 simulation test papers for self-assessment
  • Lab access to practice live during sessions
  • 24x7 learner assistance and support

Live Virtual Classes

  • Online Classroom Flexi-Pass
  • Lifetime access 
  • Practice lab and projects with integrated Azure labs
  • Access to Microsoft official content aligned to examination

One on One Training

  • Customized learning delivery model (self-paced and/or instructor-led)
  • Flexible pricing options
  • Enterprise grade learning management system (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Exam & Certification

Duration: 65 minutes (exam) + 10 minutes (Non-Disclosure Agreement/Tutorial)

Number of Questions: 40

Format: Single-choice and multiple-choice questions

Passing Score: 70% 


R Programming


R programming is a language that was developed by Ross Ilhaka and Robert Gentleman in 1993. It is a statistical and graphical language that includes machine learning algorithms, linear regression, time series, and statistical inference. This free R programming course will help you learn about the data analysis aspect of R.

Glassdoor has ranked Data Science as the best job in America 3 years in a row, with a median base salary of $110000 and 4,524 job openings. This demand is only increasing year on year, making it the fastest growing tech employment area today. Jobs that require knowledge of data science include Data scientist, Analytics Manager, Database Administrator, Data Engineer, Business Intelligence Developer etc. This course will help you learn the R programming language which is one of the most commonly used languages in the Data Science space.

Your instructors are R experts who have years of industry experience.