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Home > Training
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R Programming Training

R Programming Training

Course#: WA2324
Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning.


OBJECTIVES
This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many handson labs which allow attendees to immediately apply their theoretical knowledge in practice.
TOPICS
 High octane introduction to R programming
 Learning about R data structures
 Working with R functions
 Statistical data analysis with R
 Supervised and unsupervised machine learning with R
AUDIENCE
Business Analysts, Technical Managers, and Programmers
PREREQUISITES
Participants should have the general knowledge of statistics and programming
DURATION
2 Days 

Outline of WA2324 R Programming Training
CHAPTER 1. INTRODUCTION
 Installing R
 Character Terminal and GUI Interfaces to R
 Other GUI Integrated Development Environments
CHAPTER 2. WORKING WITH R
 Running R
 Learning GUI Integrated Development Environment
 Interacting with R Interpreter
 R Sessions and Workspaces
 Saving Your Workspace
 Loading Your Workspace
 Removing Objects in Workspace
 Getting Help
 Getting System Information
 Standard R Packages
 Loading Packages
 CRAN (The Comprehensive R Archive Network)
 Extending R
CHAPTER 3. R SYNTAX
 General Notes on R Commands and Statements
 Variables
 Assignment Operators
 Arithmetic Operators
 Logical Operators
CHAPTER 4. R DATA STRUCTURES
 R Objects
 Vectors
 Logical Vectors
 Character Vectors
 Creating and Working with Vectors
 Lists
 Creating and Working with Lists
 Matrices
 Creating and Working with Matrices
 Data Frames
 Creating and Working with Data Frames
 Interactive Creation of Data Frames
 Getting Info about a Data Frame
 Sorting Data in Data Frames
 Matrices vs Data Frames
CHAPTER 5. FUNCTIONS
 Using R Common Functions
 Numeric Functions
 Character / String Functions
 Date and Time Functions
 Other Useful Functions
 Applying Functions to Matrices and Data Frames
 Type Conversion
 Creating and Using UserDefined Functions
CHAPTER 6. CONTROL STATEMENTS
 Conditional Execution
 Repetitive Execution
CHAPTER 7. SCRIPTS
 Creating Scripts
 Loading and Executing Scripts
 Batch Execution Mode
CHAPTER 8. INPUT / OUTPUT
 Reading Data from Files
 Writing Data to Files
 Getting the List of Files in a Directory
 Diverting System Output to a File
CHAPTER 9. DATA IMPORT AND EXPORT
 Import and Export Operations in R
 Working with CSV Files
 Reading Data from Excel
 Exporting Data in SPSS Data Format
CHAPTER 10. R STATISTICAL COMPUTING FEATURES
 Basic Statistical Functions
 Writing Your Own skew and kurtosis Functions
 Generating Normally Distributed Random Numbers
 Generating Uniformly Distributed Random Numbers
 Using the summary() Function
 Math Functions Used in Data Analysis
 Correlations
 Testing Correlation Coefficient for Significance
 Regression Analysis
 Types of Regression
 Simple Linear Regression Model
 LeastSquares Method (LSM)
 LSM Assumptions
 Fitting Linear Regression Models in R
 Confidence Intervals for Model Parameters
 Multiple Regression Analysis
 Finding the BestFitting Regression Model
 Comparing Regression Models with anova and AIC
CHAPTER 11. DATA VISUALIZATION
 R Graphics
 Graphics Export Options
 Creating Bar Plots in R
 Using barplot() with Matrices
 Stacked vs Juxtaposed Layouts
 Customizing Plots
 Histograms
 Building Histograms with hist()
 Pie Charts
 Generic XY Plotting
 Dot Plots
CHAPTER 12. DATA SCIENCE ALGORITHMS AND ANALYTICAL METHODS
 Supervised and Unsupervised Machine Learning Algorithms
 kNearest Neighbors
 Monte Carlo Simulation


Address 
Start Date 
End Date 
Instructor Led Virtual 
10/23/2017 
10/24/2017 


We regularly offer classes in these and other cities. Atlanta, Austin, Baltimore, Calgary, Chicago, Cleveland, Dallas, Denver, Detroit, Houston,
Jacksonville, Miami, Montreal, New York City, Orlando, Ottawa, Philadelphia, Phoenix, Pittsburgh, Seattle, Toronto, Vancouver, Washington DC.

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10/23/2017 
Online Virtual
$1,395.00
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