Data Science with R - Itronix Solutions

Data Science with R

Learn how to use DataScience with R from beginner level to advanced techniques which is taught by experienced working professionals. With our DataScience with R Training  you’ll learn concepts in expert level with practical manner.

CHAPTER 1: Introduction

  • What is R?
  • Why R?
  • Installing R
  • R environment
  • How to get help in R
  • R console and Editor
  • Packages in R
  • CRAN
  • How to check package by date
  • Variables
  • Data Types
  • Data structure
  • Factors
  • Converting variable types
  • Missing values

CHAPTER 2: Importing and Exporting in R

  • Loading data from file(Text,Csv,Excel)
  • Loading data from clipboard
  • Connecting MySQL in R
  • How to remove lines while importing
  • Saving R data format
  • Exporting in R(Excel,Text)

CHAPTER 3: Data cleaning process:

  • Concentrating strings
  • Find and replace
  • How to split string
  • Position based spliting
  • Semi matching condition
  • Condition based row/column selection
  • Renaming column names
  • Trim

CHAPTER 4: Data manipulation

  • Data sorting
  • Find and remove duplicates record
  • Recoding data
  • Merging data
  • Data aggregation
  • User defined functions
  • Local and global variables
  • Date and Time format in R
  • Table function

CHAPTER 5:Loops:

  • For
  • If else
  • While
  • Break
  • Next
  • Return

CHAPTER 6: Visualization in R:

  • Bar, stacked bar chart
  • Pie chart
  • Line chart
  • Scatter plot
  • Histogram
  • Column chart
  • Doughnut chart
  • Trending visualization charts in R

CHAPTER 7: Advanced concept

  • Social media analysis(Twitter)through API
  • Web apps in R

CHAPTER 8:Statistics and machine learning:

  • Standard deviation
  • Outlier
  • Linear regression
  • Multiple regression
  • Logistic regressions
  • Chi square
  • Anova
  • Clustering
  • Correlation
  • Decision tree
  • K-NN Algorithm