Data Science with R Training

Data Science with R Syllabus

Introduction to R

  • What is R?
  • Why R?
  • Installing R
  • R environment
  • How to get help in R
  • R Studio Overview

Understanding R data structure

  • Variables in R
  • Scalars
  • Vectors
  • Matrices
  • List
  • Data frames
  • Cbind,Rbind, attach and detach functions in R
  • Factors
  • Getting a subset of Data
  • Missing values
  • Converting between vector types

Importing data

  • Reading Tabular Data files
  • Reading CSV files
  • Importing data from excel
  • Loading and storing data with clipboard
  • Accessing database
  • Saving in R data
  • Loading R data objects
  • Writing data to file
  • Writing text and output from analyses to file

Manipulating Data

  • Selecting rows/observations
  • Rounding Number
  • Creating string from variable
  • Search and Replace a string or Number
  • Selecting columns/fields
  • Merging data
  • Relabeling the column names
  • Data sorting
  • Data aggregation
  • Finding and removing duplicate records

Using functions in R

  • Apply Function Family
  • Commonly used Mathematical Functions
  • Commonly used Summary Functions
  • Commonly used String Functions
  • User defined functions
  • local and global variable
  • Working with dates

R Programming

  • While loop
  • If loop
  • For loop
  • Arithmetic operations

Charts and Plots

  • Box plot
  • Histogram
  • Pie graph
  • Line chart
  • Scatterplot
  • Developing graphs
  • Cover all the current trending packages for Graphs

Machine Learning Algorithm:

  • Sentiment analysis with Machine learning
  • C 5.0
  • Support vector Machines
  • K Means
  • Random Forest
  • Naïve Bayes algorithm

Statistics:

  • Correlation
  • Linear Regression
  • Non Linear Regression
  • Predictive time series forecasting
  • K means clustering
  • P value
  • Find outlier
  • Neural Network
  • Error Measure

Leading Topics:

  • Overture of R Shiny
  • What is Hadoop
  • Integration of Hadoop in R
  • Data Mining using R
  • Clinical research preface in R
  • API in R (Twitter and Facebook)
  • Word Cloud in R
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