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Best R Programming Training Institute in Delhi NCR

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What is R Programming ?

Join Best R Programing Training in Delhi, R Programing Training Course in Delhi, R Programing Training Institute in Noida

CETPA INFOTECH is the leading training institute in Northern India providing R Programming training as well as training in other cutting edge technologies. It is the best R programming Training in Delhi NCR R is a programming language for statistical analysis, reporting, and graphics representation. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac. Due to its expressive syntax and easy-to-use interface, it has grown in popularity in recent years.

CETPA has been awarded as “Best IT and Embedded Training Company” for 5 consecutive years. It delivers high-quality R Programming training in Noida according to the international standards. This course has been especially designed to prepare students for a job in the analytics space. This training is delivered on the short duration as well as long term basis. Any technical student or corporate person can join this training. This training is especially beneficial for-

Graduates who want to build career in this field.
Professionals working in data science and analytics industry.
Professionals looking for a career switch into data science and analytics.

The company has designed training programs for both students and professionals separately. R Programming course with CETPA provides an extensive coverage of a number of advanced R Programming concepts and their implementation in real-time projects. The training offers hands-on experience with a number of common R Programming concepts.

With world-class infrastructure and a dynamic team of experienced faculty, CETPA provides the R Programming training in Noida. After completion of the R Programming program at CETPA, the students are awarded a global Certificate which is recognized as well as accepted not only in India but also in foreign countries. The training process at CETPA comprises of both classroom as well as practical sessions which will make students capable of handling complex and difficult situation when they would join the corporate world.

Training in R programming is available on weekdays as well as weekends. Special Classes can also be scheduled as per requirement.It is the best R programming Training institute in Delhi NCR. Its industry-focused curriculum is in line with the international standards to make sure that the training prepares our students for jobs not just in India but foreign countries too. Apart from that, it makes all its efforts to provide placement in top MNC’s to its certified students.

Other benefits of training CETPA-

Hands-on Mode of Teaching as well as opportunity to work on live projects.
100% Placement Support for all Students
Proficient and Skilled Trainers from the Industry
Flexible Batch Timings
Small Batch Size for individual attention
1 year Membership Card

ARE YOU LOOKING FOR EXCITING OFFERS FOR r programming COURSE IN NOIDA?

Answer

To avail exiting offers and discount on our r programming training program, you can mail us at query@cetpainfotech.com or call us at 120- 4535353. You can also visit our center to get your query resolved.

WHICH IS THE BEST INSTITUTE TO LEARN r programming IN NOIDA?

Answer

CETPA Infotech, an ISO 9001:2015 certified training company is the best option to learn r programming. Since, they provide job based training and their training curriculum is at par with industrial criteria.

WHAT IS THE DURATION & FEE OF r programming COURSE?

Answer

The duration of r programming course depend on type of training mode you opt for, i.e. Weekday batch, Weekend batch, fast track batch or online batch. For free structure, you can visit our centre or call us at 120- 4535353.

WHAT IS THE SCOPE OF r programming?

Answer

r programming is one of the fastest growing languages and has undergone a successful span of more than 25 years as far as its adoption is concerned. This success also reveals a promising future scope of r programming programming language.

HOW DO I BECOME A r programming EXPERT?

Answer

Becoming a r programming programmer can be difficult for beginners, especially for those who have no experience of coding. By joining our r programming Training, you can start learning the language

WHO SHOULD TAKE THIS r programming TRAINING COURSE?

Answer

This training is suitable for fresher, graduates as well as post graduates. If you are a professional who want to polish your skill, then also you can join this training.

WHAT ARE THE PREREQUISITES FOR THIS r programming LEARNING COURSE?

Answer

Anyone who has the passion to learn r programming can join our training program.

WHO IS MY TRAINER AND HOW ARE THEY SELECTED?

Answer

CETPA has a team of highly experienced industrial experts who have sound knowledge of their domain and will assist you in completion of your live project.

WHAT ARE THE DIFFERENT MODES OF r programming TRAINING THAT CETPA PROVIDES?

Answer

Classroom Training
Online Training
Corporate Training
On campus Training

WHAT ARE THE PAYMENT OPTIONS?

Answer

We accept all the major payment modes like Cash, Card (Master, Visa, and Maestro, etc), Net Banking and etc. UPI, Paytm, etc.

I HAVE MORE QUERIES?

Answer

To get more information, you can mail us at query@cetpainfotech.com or call us at 120-4535353. You can also visit our center to get your query resolved.

Download Course Content

Module 1: Essential to R programming

An Introduction to R

History of S and R
Introduction to R
The R environment
What is Statistical Programming?
Why use a command line?
Your first R session

Introduction to the R language

Starting and quitting R
Recording your work
Basic features of R
Calculating with R
Named storage
Functions
Exact or approximate?
R is case-sensitive
Listing the objects in the workspace
Vectors
Extracting elements from vectors
Vector arithmetic
Simple patterned vectors
Missing values and other special values
Character vectors
Factors
More on extracting elements from vectors
Matrices and arrays
Data frames
Dates and times
Built-in functions and online help
Built-in examples
Finding help when you don’t know the function name
Built-in graphics functions
Additional elementary built-in functions
Logical vectors and relational operators
Boolean algebra
Logical operations in R
Relational operators
Data input and output
Changing directories
dump() and source()
Redirecting R output
Saving and retrieving image files
Data frames and the read.table function

Programming statistical graphics

High-level plots
Bar charts and dot charts
Pie charts
Histograms
Box plots
Scatterplots
QQ plots
Choosing a high-level graphic
Low-level graphics functions
The plotting region and margins
Adding to plots
Setting graphical parameters

Programming with R

Flow control
The for() loop
The if() statement
The while() loop
Newton’s method for root finding
The repeat loop, and the break and next statements
Managing complexity through functions
What are functions?
Scope of variables
Miscellaneous programming tips
Using fix()
Documentation using#
Some general programming guidelines
Top-down design
Debugging and maintenance
Recognizing that a bug exists
Make the bug reproducible
Identify the cause of the bug
Fixing errors and testing
Look for similar errors elsewhere
The browser() and debug()functions
Efficient programming
Learn your tools
Use efficient algorithms
Measure the time your program takes
Be willing to use different tools
Optimize with care

Simulation

Monte Carlo simulation
Generation of pseudorandom numbers
Simulation of other random variables
Bernoulli random variables
Binomial random variables
Poisson random variables
Exponential random numbers
Normal random variables
Monte Carlo integration
Advanced simulation methods
Rejection sampling
Importance sampling

Computational linear algebra

Vectors and matrices in R
Constructing matrix objects
Accessing matrix elements; row and column names
Matrix properties
Triangular matrices
Matrix arithmetic
Matrix multiplication and inversion
Matrix inversion
The LU decomposition
Matrix inversion in R
Solving linear systems
Eigenvalues and eigen vectors
Advanced topics
The singular value decomposition of a matrix
The Choleski decomposition of a positive definite matrix
The QR decomposition of a matrix
The condition number of a matrix
Outer products
Kronecker products
apply()

Numerical optimization

The golden section search method
Newton–Raphson
The Nelder–Mead simplex method
Built-in functions
Linear programming
Solving linear programming problems in R
Maximization and other kinds of constraints
Special situations
Unrestricted variables
Integer programming
Alternatives to lp() Quadratic programming

Module 2: Data Manipulation Techniques using R programming

Data in R

Modes and Classes
Data Storage in R
Testing for Modes and Classes
Structure of R Objects
Conversion of Objects
Missing Values
Working with Missing Values

Reading and Writing Data

Reading Vectors and Matrices
Data Frames: read.table
Comma- and Tab-Delimited Input Files
Fixed-Width Input Files
Extracting Data from R Objects
Connections
Reading Large Data Files
Generating Data
Sequences
Random Numbers
Permutations
Random Permutations
Enumerating All Permutations
Working with Sequences
Spreadsheets
The RODBC Package on Windows
The gdata Package (All Platforms)
Saving and Loading R Data Objects
Working with Binary Files
Writing R Objects to Files in ASCII Format
The write Function
The write.table function
Reading Data from Other Programs

R and Databases

A Brief Guide to SQL
Navigation Commands
Basics of SQL
Aggregation
Joining Two Databases
Subqueries Modifying Database Records
ODBC
Using the RODBC Package
The DBI Package
Accessing a MySQL Database
Performing Queries
Normalized Tables
Getting Data into MySQL
More Complex Aggregations

Dates

as.Date
The chron Package
POSIX Classes
Working with Dates
Time Intervals
Time Sequences

Factors

Using Factors
Numeric Factors
Manipulating Factors
Creating Factors from Continuous Variables
Factors Based on Dates and Times
Interactions

Subscripting

Basics of Subscripting
Numeric Subscripts
Character Subscripts
Logical Subscripts
Subscripting Matrices and Arrays
Specialized Functions for Matrices
Lists
Subscripting Data Frames

Character Manipulation

Basics of Character Data
Displaying and Concatenating Character
Working with Parts of Character Values
Regular Expressions in R
Basics of Regular Expressions
Breaking Apart Character Values
Using Regular Expressions in R
Substitutions and Tagging

Data Aggregation

Table
Road Map for Aggregation
Mapping a Function to a Vector or List
Mapping a function to a matrix or array
Mapping a Function Based on Groups
There shape Package
Loops in R

Reshaping Data

Modifying Data Frame Variables
Recoding Variables
The recode Function
Reshaping Data Frames
The reshape Package
Combining Data Frames
Under the Hood of merge

Module 3: Statistical Applications using R programming

Basics

First steps
An overgrown calculator
Assignments
Vectorized arithmetic
Procedures
Graphics
R language essentials
Expressions and objects
Functions and arguments
Vectors
Quoting and escape sequences
Missing values
Functions that create vectors
Matrices and arrays
Factors
Lists
Data frames
Indexing
Conditional selection
Indexing of data frames
Grouped data and data frames
Implicit loops
Sorting

The R environment

Session management
The workspace
Textual output
3 Scripting
Getting help
Packages
Built-in data
attach and detach
subset, transform, and within
The graphics subsystem
Plot layout
Building a plot from pieces
Using par
Combining plots
R programming
Flow control
Classes and generic functions
Data entry
Reading from a text file
Further details on read.table
The data editor
Interfacing to other program

Probability and distributions

Random sampling
Probability calculations and combinatorics
Discrete distributions
Continuous distributions
The built-in distributions in R
Densities
Cumulative distribution functions
Quantiles
Random numbers

Descriptive statistics and graphics

Summary statistics for a single group
Graphical display of distributions
Histograms
Empirical cumulative distribution
Q–Q plots
Boxplots
Summary statistics by groups
Graphics for grouped data
Histograms
Parallel boxplots
Stripcharts
Tables
Generating tables
Marginal tables and relative frequency
Graphical display of tables
Barplots
Dotcharts
Piecharts

One- and two-sample tests

One-sample t test
Wilcoxon signed-rank test
Two-sample t test
Comparison of variances
Two-sample Wilcoxon test
The paired t test
The matched-pairs Wilcoxon test

Regression and correlation

Simple linear regression
Residuals and fitted values
Prediction and confidence bands
Correlation
Pearson correlation
Spearman’s ρ
Kendall’s τ

Analysis of variance and the Kruskal–Wallis test

One-way analysis of variance
Pairwise comparisons and multiple testing
Relaxing the variance assumption
Graphical presentation
Bartlett’s test
Kruskal–Wallis test
Two-way analysis of variance
Graphics for repeated measurements
The Friedman test
The ANOVA table in regression analysis

Tabular data

Single proportions
Two independent proportions
k proportions, test for trend
r × c tables

Power and the computation of sample size

The principles of power calculations
Power of one-sample and paired t tests
Power of two-sample t test
Approximate methods
Power of comparisons of proportions
Two-sample problems
One-sample problems and paired tests
Comparison of proportions

Advanced data handling

Recoding variables
The cut function
Manipulating factor levels
Working with dates
Recoding multiple variables
Conditional calculations
Combining and restructuring data frames
Appending frames
Merging data frames
Reshaping data frames
Per-group and per-case procedures
Time splitting

Multiple Regression

Plotting multivariate data
Model specification and output
Model search

Linear models

Polynomial regression
Regression through the origin
Design matrices and dummy variables
Linearity over groups
Interactions
Two-way ANOVA with replication
Analysis of covariance
Graphical description Comparison of regression lines Diagnostics

Logistic regression

Generalized linear models
Logistic regression on tabular data
The analysis of deviance table
Connection to test for trend
Likelihood profiling
Presentation as odds-ratio estimates
Logistic regression using raw data
Prediction
Model checking

Survival analysis

Essential concepts
Survival objects
Kaplan–Meier estimates
The log-rank test
The Cox proportional hazards model

Rates and Poisson regression

Basic ideas
The Poisson distribution
Survival analysis with constant hazard
Fitting Poisson models
Computing rates
Models with piecewise constant intensities

Nonlinear curve fitting

Basic usage
Finding starting values
Self-starting models
Profiling
Finer control of the fitting algorithm

What are the benefits of doing a R Programming course?

You will get better knowledge of programming and how to implement it for actual development requirements in the industrial projects and applications.
Enhanced knowledge on the web development framework. Using this framework, you can develop dynamic websites swiftly.
You will learn how to design, develop, test, support and deploy desktop, custom web, and mobile applications.
Design and improve testing and maintenance activities and procedures.
Design, implement and develop important applications in a R Programming environment.
Increased chances of working in leading software companies like Infosys, Wipro, Amazon, TCS, IBM and many more.

Aiswarya Saxena

Best R Programming Training in Noida

October 10 2018

Just completed my training from Cetpa in R programming and currently working for DXC technology. A big thanks to my trainer.

Mode/Schedule of Training:

CETPA, The Best R Programming Training Institute in Delhi NCR offers courses in following modes.

Delivery Mode	Location	Course Duration	Schedule (New Batch Starting)
Classroom Training (Regular/ Weekend Batch)	Noida/ Lucknow Dehradun /Roorkee	4/6/12/24 weeks	New Batch Wednesday/ Saturday
*Instructor -Led Online Training	Online	40/60 Hours	Every Saturday or as per the need
*Virtual Online Training	Online	40/60 Hours	24x7 Anytime
College Campus Training	India or Abroad	40/60 Hours	As per Client’s need
Corporate Training (Fly a Trainer)	Training in India or Abroad	As per need	Customized Course Schedule

Professional growth, increased compensation and validation of the skill are the most popular reasons why individuals and professionals seek IT certifications. Keeping this in mind, we at CETPA provide you with certification in latest and innovative technologies to help you to reach your certification goals.

CETPA is the official Training partner of Oracle, Microsoft, Autodesk, Panasonic and Nuvoton and thus provides Training as per international standards and curriculum. CETPA proudly provides you certification in association with our training partners so that you can validate your domain specific technical skills. Certification from these big brands will help you in grabbing your dream job.

IMPORTANCE OF CETPA CERTIFICATION

For individuals and IT professionals:

Gives you an advantage while searching for a job and provide a competitive advantage over your competitors.
Ensure knowledge and skill are up to date and can be applied to the job
Provide credibility to those looking for a career in an IT domain.
Offer fast track to career advancement
Demonstrate level of competency
Professional Credibility as well as it demonstrates your dedication and motivation to professional development.
You are likely to stand out from the crowd and be considered to be successful in your positions.
Represent a well-recognized and valued IT credential that increases marketability and competitive edge.

For organizations:

Provide peace of mind with the confidence that certified employees have truly learned the skills necessary to do their jobs;
Express valuable credentials to search for in prospective employees, and can help retain top performers when offered as an incentive;
Offer a competitive advantage when the team is trained and certified regularly.