Best R Programming Training in Gurgaon & Best R Programming Training Institute in Gurgaon

Best r-programming training institute in gurgaon
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Join Best R Programming Training in Gurgaon, R Programming Course in Gurgaon, R Programming Institute in Gurgaon

APTRON delivers an in-depth best R Programming training in gurgaon. Students having R Programming certification are able to secure a quick job in an MNC. Participants need to enroll in a best R Programming training institute in gurgaon to attain the skills involved in the technology. Our core strength is our trainers, who are expert professionals and veteran from the industry. At R Programming institute in gurgaon, our trainers have developed practical modules combining the syllabus (industry compliance). During the R Programming course in gurgaon, trainers create realistic situation using simulators and devices.

R Programming training classes students are asked to take decision concerning to troubleshooting or managing the technology without interrupting the running business operations. Join the best R Programming training in gurgaon provided by APTRON Gurgaon which equip participants with thorough information, knowledge and experience on the subject.

At APTRON, we consider students as our responsibility. Our values inspire us to provide students a comprehensive R Programming training so that they achieve their career goals confidently. To do that, we have setup a laboratory in accordance to industry standards that comprises of latest devices, applications and softwares. Our whole building is equipped with Wi-Fi facility, latest I.T infrastructure, and smart classroom facilities.

Our responsibility does not end after completion of R Programming course and certification. We provide R Programming training course with placement solution to the students. Our placement team schedule placement drives and also conducts interview in different MNCs. Already, we have kept a moderate R Programming course fee to support students coming from all sections of the society. Further, students find the R Programming training course duration flexible. R Programming course time is scheduled according to the student's requirements.

APTRON Gurgaon R Programming is all about practical and practice; our classes include theory and practical exposure for the students in learning. Join the best R Programming training in gurgaon provided by APTRON Gurgaon to avail quick R Programming coaching, moderate course fee, and placement after Ab initio course.

The R Programming syllabus includes for R Programming course module on real time projects along with placement assistance. R Programming topics covered are Introduction to R Programming, Statistical Programming, Programming statistical graphics, Simulation, Computational linear algebra, Numerical optimization, Data Manipulation Techniques using R programming, R and Databases, Subscripting, Data Aggregation, Statistical Applications using R programming & Many more. Check the duration, course content and syllabus given below.

R Programming Course Fee and Duration

Track Regular Track Weekend Track Fast Track
Course Duration 45 - 60 Days 8 Weekends 5 Days
Hours 2 hours a day 3 hours a day 6+ hours a day
Training Mode Live Classroom Live Classroom Live Classroom

Course Content Covered in R Programming Training Course

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 eigenvectors
  • 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
  • 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 programs
  • 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 ?
  • Kendall’s ?
  • 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

Top Reasons to Choose APTRON for R Programming Training in Gurgaon

  • Our R Programming training in gurgaon adheres to international industry standards.
  • We facilitate students with modern I.T infrastructure and learning environment during the R Programming training in gurgaon.
  • Trainers in R Programming training classes combine the self-developed practice session module with current syllabus.
  • Being responsible, we provide students R Programming course with placement assistance.
  • R Programming training in gurgaon is conducted during weekdays and weekends as per participant's needs.
  • Our R Programming trainers are analysts, researchers, consultants and managers possessing a decade experience in coaching R Programming course in gurgaon.
  • Ultra-modern I.T laboratory equipped with latest infrastructure.
  • Our lab is opened 365 days in a year. Students are facilitated with online mentoring during practice sessions.
  • R Programming training classrooms are equipped with projectors, live racks, Wi-Fi, and digital pads.
  • We facilitate students with glass-door study room and discussion zone area (meeting room).
  • No cost training sessions are conducted on personality development, spoken English, group discussion, and mock interview to sharpen the presentation skills.
  • No cost R Programming training course materials are provided.
  • Study materials include books, and soft copies of tutorials in the form of PDFs, sample papers, technical and HR interview questions.
  • We also provide hostel facility at Rs.4,500/- a month.
  • Our certificates are globally recognized provided after completion of course.
  • We facilitate students with Extra Time Slots (E.T.S) for doing unlimited practical at no cost..
  • According to the requirements, students can retake the class at no cost.
  • To enhance knowledge of the students, the complex technical concepts are imparted through easy coaching.
  • We accept master and visa cards (Debit & Credit), also payment mode cash, cheque, and Net Banking available.

APTRON Trainer's Profile for R Programming Training in Gurgaon

APTRON'S R Programming Trainers are:

  • Our trainers are subject specialist who have mastered on R Programming technology.
  • Our trainers are have received excellence awards for their dedicated R Programming training and coaching.
  • Our trainers are researchers, consultant, and analysts working as an employee in HCL Technologies, Birla-soft, TCS, IBM, Sapient, Agilent Technologies, and so on.
  • Our trainers are single, double and triple certified professionals in the subject.
  • Our trainers have regular coordination with MNCs HR team on daily basis.

Placement Assistance after R Programming Training in Gurgaon

APTRON'S Placement Assistance

  • APTRON's Gurgaon division having successful 96% placement rate.
  • APTRON’s R Programming training centre in Gurgaon assist students in writing their resume meeting the current industry needs.
  • APTRON’s R Programming training institute in Gurgaon sharpens students’ interview skills, provide session on personality development, spoken English, group discussion, mock interview, and presentation.
  • APTRON, the best R Programming training institute in Gurgaon assists students in securing placement in top IT firms such as HCL, TCS, Infosys, Wipro, Accenture, etc., confidently.

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R Programming Training in Gurgaon Reviews

R Programming Training in Gurgaon
Reviewed by
Rashida
on
APTRON training is remarkable training center in Gurgaon for R Programming with organized course-ware. I am quite sure that I will get R Programming profession job shortly.

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R Programming training in Gurgaon
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on
APTRON institute is brilliant training center for R Programming certification. You will get the impeccable R Programming certification training in Gurgaon.

Rating:
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R Programming Training Institute in Gurgaon
Reviewed by
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on
I got trained in R Programming certification from APTRON training institute in Gurgaon, got trained in course very well. Waiting for R Programming certification placement.

Rating:
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R Programming training in Gurgaon
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on
APTRON training center is suggested by my brother for the most excellent R Programming training in Gurgaon. I like the practical training classes for R Programming course.

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on
APTRON training center in Gurgaon is recommend by one of my friend. I have finished R Programming training and now I am attending interviews.

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