R Programming

What is R

R programming is the world’s most powerful programming language and software environment for statistical computing and graphics. R programming is free, open-source software distributed and maintained by the R-project. The source code is available under the terms of the Free Software Foundation's GNU General Public License for a variety of platforms. R programming offers extensive analytics capabilities ranging from Text Analytics, Predictive, Time Series, Optimization and contains a number of built- in mechanisms for organizing data, running calculations on the information and creating graphical representation of data sets. R programming is one of the most commonly used languages when it comes to data analyzing/statistical software development.

Why R

  • R Programming language is an open source and completely an interactive object oriented Language
  • R can run on several operating systems
  • Rich functionality in R Programming language helps developers to create tools and methods
  • R has superlative graphical capabilities, providing programmable graphics.
  • R is a language which helps non IT students become a developer.
  • R Programming language is used by the Companies like Google, Microsoft, and Mozilla Firefox and more
  • R Programming language can create reproducible and high-quality analysis
  • R Programming language has an extraordinary mechanism to create data structures.

Highlights of R Programming Language

  • R programming is the highest paid IT skill, with increasing demand and over 2.5 million users worldwide.
  • 70% of Data Miners use R
  • Ranked #15 in all Programming Language.

R programming best suits the following audience

  • Programmers wanting to shift to analytics
  • Data and Business analytics professionals
  • IT & Non IT graduates looking to build a career in data analysis.

R Basics

Introduction to R
  • R-studio
  • Packages in R
  • Installing packages
  • Settings Directory
Data types
  • Character
  • Factor
  • Integer
  • Float
  • Date and time
Basic Operations in R
  • Programming Language basic
  • Scalars
  • Vectors
  • Simple calculation data structures
  • Data frame
Data Manipulation
  • Data acquisition
  • Sub-setting observation & variables
  • Transforming Variables
  • Conditional processing
  • Merging & concatenating data sets
  • Using SQL in R
Statistics Using R
  • Basic statics in R
  • Descriptive statistics
  • Cross tabs
  • T-test
  • ANOVA
  • N-way ANOVA
  • Correlation Sampling
  • Bootstrapping random number generation
Graphics in R
  • Line plots
  • Bar charts
  • Pie charts
  • Histograms
  • Scatter Plots
  • 3D parallel coordinates
Linear models in R
  • Simple regression analysis
  • Multiple regressions
Logistic Regression in R
  • Logic functions
  • Maximum likelihood optimization
  • Odds ratio
Model selection in R
  • Selection criterion s
  • Step wise methods
Writing functions in R
  • Creating user defined functions
          

Advanced R

PREDICTIVE ANALYSIS

Review of basic statistics in R
  • Basic statistics (Mean, Median, S.D)
  • ANOVA (CRD, RBD)
  • Correlations
  • Outliers
  • Statistical graphics
Predictive modeling using regression analysis
  • Linear regression
  • Modeling assumptions
  • Logistic regression
  • Modeling assumption
  • Model selection
  • Scoring
Predictive modeling using decision trees analysis & random forest
  • Recursive partitioning
  • CART
  • Splitting criterion pruning
Other predictive modeling tools
  • Support vector machine
  • K-nearest neighbor algorithm
Text Analysis
  • Basic of Text Mining
  • Preparing and loading a corpus
  • Performing, Scanning, Creating & Exploring Term-Document Matrix-Gram analysis
Visualizations in Text Mining
  • Creating and modifying a word cloud, Reshaping
  • Resizing and Recoloring, Word Association analysis
Advances i text Analytics
  • Text Clustering & Categorization Sentiment Analysis

MULTIVARITE ANALYSIS

Clustering
  • Hierarchical Clustering
  • K-Means Clustering
Variable Reduction
  • Factor analysis
  • Principal Component Analysis
Association Mining
  • Market Basket Analysis
Mazenet Solution offers "R program training" in two modes. You can either visit our world class training facility in Chennai & Coimbatore or you can learn from the comfort of your own home.

R Programming Online Training

  • Learn it from anywhere and anytime
  • Interactive Live sessions
  • Maximum 5 Students per Batch
  • Training by Corporate Trainers who are certified in R language (Revolution R Enterprise Certified Specialist)
  • Flexible Timings
  • Recorded Sessions available for all the registered candidates
  • Course Completion Certificate at the time of completion
  • Online Exam based Training
  • Placement support

R Programming Classroom Training – Chennai & Coimbatore

  • Train in a ready-to-learn comfortable environment
  • Training by certified Corporate Trainers
  • Get hands-on labs, industry oriented experience
  • Week Days & Week End Batches
  • Higher end systems with R Programming software
  • Syllabus customized to meet the industry standard
  • Online Exam Training
  • Placement support

Global Certification Details

Exam Name: Revolution R Enterprise Certified Specialist. Delivery Partner: Kryterion Cost: $200 USD per test attempt No. of question: 60 (Multiple Choice) Passing Score: 70% Duration: 90 minutes
Basic knowledge in statistics and good analytical skills

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Mr. Sriram
Phone: +91 9789437777
Email: sriram@mazenetsolution.com



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