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R programming language is the language and programming environment which is commonly used in data analytics, scientific research as well as statistical computing. It is one of the most famous languages that is supported by the R Foundation for Statistical Computing that is used by the data analysts, researchers, and statisticians to present, visualize, and analyze data. In recent years, the use of the R programming language has increased massively used for the expressive syntax format as well as the easy to use interface. In the TIOBE index, the R programming language ranks in the 14th Position as of February 2020.

As the language is built for the manipulation of the statistics, it is used highly by data analysts and scientists for performing statistical computing, scientific research, and statistical computing. As the syntax of the R programming language is expressive, and the interface is easy to use, the popularity of R Programming language has increased in recent years.

TechAxis is providing R programming training in Nepal on an international standard to produce highly proficient data scientists, data analysts, and statistical computing experts. The course is designed to provide the students with the requirements to help the students deal with statistical computing issues and handle big data. 


    R programming language is a widely used language for statistical computing and graphics. It is a powerful language for data analysis, data visualization, and machine learning.

    • R is designed for data analysis and visualization. It has a wide range of tools and packages for statistical analysis, data manipulation, and visualization. It is the language of choice for many data scientists and statisticians.
    • R is an open-source language, which means it is free to use and modify. This makes it accessible to anyone who wants to learn data analysis, regardless of their budget.
    • R has a wide range of packages for machine learning, making it a popular language for data scientists and machine learning engineers.
    • R is widely used in the industry, particularly in the fields of finance, healthcare, and tech. Learning R can increase your job opportunities in data analysis, data science, and machine learning.
    • R has a large and active community of users who share their knowledge and expertise. This means that there are plenty of resources available for learning R, including online tutorials, forums, and user groups.

Course overview

R programming is the language that is used for data analysis and functional writing of the statistics. As it comes with various designs, it has a large environment. It is open-source software that provides graphic techniques along with the diverse statistics in a secure operating system. With the growing need for R programming in data manipulation and geographical display, TechAxis has come with an R programming course for individuals who are looking for R Programming training.

Why R programming?

If you have made a mind to enter into the programming platform and secure a highly paid job in a renowned IT Company, here is the best choice you can make. The R programming course is what you should seek. As the demand of the data analysts and data experts are increasing worldwide, there are a vast number of benefits that the course can serve you with. The prominent and renowned data centres, scientists, and statistical companies look for R programming. With the knowledge that you gain from the R programming course, you can rule the IT industry.

TechAxis provides the best R programming language training as it offers training from professionals. As the demand for the IT industry is increasing, it gives high priority to the candidates and provides them everything to help them receive good knowledge.

The primary benefit of the R programming language is given below

  • It makes it easier to configure as well as install Rstudio.
  • It helps you to implement the basic concepts of R Programming in advanced data analytics as well as data science.
  • It enhances the leadership skill
  • You can create an eye-catching report with it
  • It is used to develop statistical tools
  • As the demand is continuously growing, the R programming language is evolving
  • You will learn leadership skills
  • It develops professionalism
  • Great job opportunities and offers a vast career scope in the field of resource management, data analytics, data science, and social science.
  • Hence, R programming training will prove to be very useful for the individuals who are seeking opportunities in data science and data analytics.

Prerequisites of R Programming Training

Before you take the training of R Programming, you need to make sure that you know other programming languages as well. Prior experience in programming can help a lot for people trying to enter the R programming field. It can help you to capture things easily during the training session.

Career Opportunities

The career opportunities for the people with R programming courses are broad. As it is one of the most competent statistical programming languages, it can increase the overall professionalism, academics, and the career outlook of the individuals with the R programming course. The individuals can look for a job in various growing platforms like a critical analysis of data, research, data science, social science as well as critical analysis.

Teaching Methodology

  • Handful of assignments, tutorials and lab test of each chapter
  • Periodic feedback from Trainer and Trainee and do the required changes as per necessity
  • Each trainee need to develop demo application on their own, taking assistance form trainer when ever required


  • Good command in english language
  • Good knowledge of Computer, Softwares etc.
  • Basic understanding of Programming would be a plus
  • Understanding of Softwares and Software installation

Course content

courses | 2 Months

General Introduction into the R Ecosystem

  •  Downloading and installing R
  • History of R, R packages, CRAN
  • R community, R-bloggers
  • Stack Overflow, Coursera, DataCamp
  • R User Groups & meetups

Demonstration of a Data Analysis Project in R

  •  Brief Overview on R Coding Tools RStudio
  • git, Github

R Syntax Basics

  • Constants, operators, functions, variables
  • Random numbers
  • Vectors and vector indexing
  • Simple descriptive stats
  •  Loops
  • Conditional expressions

The Power of R

  • Applying PCA on an image for outlier-detection
  • Visualizing MDS on a distance matrix

A Systematic Introduction into Data Types

  • Levels of measurement (nominal, ordinal, interval, ratio scale)
  •  Vector types
  • data. frame objects, rows and columns, indexing
  •  Characteristics of tidy data

Basic Data Transformations Create new variables in a data. frame

  •  Filter rows and columns
  •  Merging datasets
  •  Introduction to data. table for More Complex Data Transformations

Filtering and ordering data

  • Summaries and aggregates
  • New variables
  • Relational data
  • Joins on Keys
  • Introduction into fuzzy joins
  • Transforming wide and long tables

EDA - First Steps with Data Visualization

  • Why not Use Pie Charts
  •  Plots outside of Excel: dot chart and violin plot examples
  •  The Grammar of Graphics in R with ggplot2
  •  Using labels for variable names

Introduction to Non-tabular Data Types

  • Time-series
  • Spatial data
  • Network data
  • Big Data Problems: What is Big Data
  • 4V: volume, variety, velocity, veracity
  • Data Transformations: Converting Numeric Variables into Factors
  • Date Operations
  • String Parsing
  • Geo coding
  • Dirty Data Problems: missing values
  • data imputation
  • duplicates
  • 4 forms of data dates
  • outliers
  • spelling

Project Work

  • Project Work 
  • Project Evaluation and Feedback.
  • Deploying Project

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