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R Programming Training In Vijayawada

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By Author: rohith go
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R Programming Training
During the last two decades, the size of data has increased exponentially worldwide and it continues to do so. This has led to an increasing demand for a data scientist to analyze and interpret this data as well as tools to help the data scientist in their analysis. R programming is one of the most influential languages and tool for statistical analysis of data which is used by data scientists, analysts as well as business professionals and non-software engineers who want to interpret data. CodeGnan is a leading R programming training in Vijayawada which helps individuals to learn this language.

What is the R Programming?
R is not only a language but also an environment for statistical computing and design. It was initially developed in 1993 by Ross Ihaka and Robert Gentleman, but since then it has come a long way in terms of improved efficiency and ease of use. It contains an extensive list of statistical and graphical methods to analyze, represent, and report data. R language training offers you a chance to learn a well-developed, simple, and effective programming language which includes conditionals, loops, user defined recursive functions, and input-output facilities. An R language training institute such as CodeGnan also teaches you effective data handling and storage facility.

Using R Programming
Some other things that you would learn in an R programming training on Vijayawada are:

A suite of operators for mathematical calculations on matrices, vectors, lists, and arrays;
R course training would also enable you to use large, coherent, and integrated collection of tools for data analysis;
R training Institute also teaches you graphical facilities in R for data analysis and display by printing or on a computer.
Steps in R Language
R programming training in Vijayawda by CodeGnan teaches data analysis with R as a series of steps, which are:

Program: R is an accessible and clear programming tool;
Transform: R contains a collection of libraries which are designed specifically for data science;
Discover: This is the stage in R language training which enables you to investigate the data, refine your hypothesis, and analyze them.
Model: R provides a wide range of tools for you to capture the right model for the sample data;
Communicate: At this stage of R programming training, you will be able to integrate codes, graphs, and output to a report.
Why should you choose to learn R Language?
Admittedly, there are other languages as well which can help you to analyze data. So why should you choose to learn R instead of those?

R is the best platform for statistics, data analysis, and machine learning. R course training will teach you more than just a statistical package; rather you will be able to create your own objects, functions, and packages.
R can quickly try several ideas and factual issues by explicitly recording the actions of analysis and making it easy to reproduce and update report.
R can be used anywhere as it is platform independent and can be applied to any operating system. Because it is a free platform, you can implement it in any organization without having to purchase a license.
In addition to being a free programming language, it is also open source. This means that after completing your course from an R training institute, you will be able to examine the source code to check its functions. It also means that you will be able to fix bugs and add features rather than waiting for the vendor to do so in a future release.
R programming also allows you to integrate with other languages such as C/C++, Python, Java, and enables you to communicate with various data sources such as Excel, access, and statistical packages such as Stata, Minitab, etc.
R Language also serves as glue for piecing together various data sets, tools, and software packages.
An R language training institute would also teach you to create reproducible, excessive quality analysis by R programming as it has much flexibility and power which is required while dealing with big data.
Moreover, it is utilized in nearly all industries. It is used the most in academic and Healthcare industries. Followed by Government agencies, consulting, insurance, energy, finance, retail, and many other industries.
Finally, tech giants such as Google are utilizing R programming.
Why CodeGnan to be chosen to learn R Programming training in Vijayawada?
CodeGnan provides many hours of top-notch R programming training in Vijayawada. This course is divided into several parts to ensure that you understand each step of the R language effectively before moving onto the next step. We are the best R programming training in Vijayawada as we have the best faculty and resources to provide you classroom and hands-on training. By the end of the course, you will have extensive knowledge of using R language to analyze, represent, and report big data.

CURRICULUM
Course Syllabus
Z
Chapter 1 - Introduction to Business Analytics
Introduction to Business Analytics & it’s Features
Types of Business Analytics
Business Analytics Case Studies
Business Decisions
Business Intelligence
Data Science and it’s importance
Z
Chapter 2 - Introduction to R
Introduction to R
Understanding R
Using R to illustrate the basic concepts
Installing R and RStudio
Integrated Development Environments (IDEs) for R
Using R Console
Scripting in R
R Workplace and Packages
Distributed R
Introduction
Installation
Programming Concepts
Z
Chapter 3 - R Programming
Introduction
Operators in R(Arithmetic, Relational, Logical, Assignment)
Basic and Advance Data Types
Loops and Conditional Statement in R
Commands to Run an R Script and a Batch Script
Functions in R
String Manipulation in R
Dplyr Package – An Overview
Installing Dplyr
Functions of the Dplyr package
Z
Chapter 4 - R Data Structure
Types of Data Structures in R
Vectors
Scalars
Matrices
Arrays
Data Frames
Factors
Lists
Elements of the Different Data Structures in R
Acceptable Formats to Import and Export Data in R
Z
Chapter 5 - Data Visualisation
Graphics in R
Types of Graphics
Basic elements of graph
Methods to Save Graphics as Files
Procedure to Export Graphs in RStudio
Z
Chapter 6 - R Connection with Database
Introduction to RDBMS
Introduction to MySql
R packages to connect to database
Data analysis of data from database
Z
Chapter 7 - Debugging in R
Introduction to Debugging
Important function to Debug
Z
Chapter 8 - Statistics in R
Introduction to Statistics
Types of Data
Qualitative vs Quantitative Analysis
Hypothesis Testing in R
Need of Hypothesis Testing in Business
Test of mean
Test of variance
Chi-square Test
Non-parametric Test
Linear Regression
Basics of Classification
Basics of Clustering

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