Data Science with R Online Training

Data Science with R Online Training

Data-science-with-r-language-nareshit

About Data Science with R Online Training

R is an open source programming language. It combines Big data analysis, Simulation, graphics, etc. It is the leading and most flexible programming language. Also it is the most powerful. By using R the data science is more flexible. The Data Science with R combines a Statistical Modeling. By using R the Data Science is gaining on big-data analysis packages due to flexibility. Also, provides documentation and open-source.

Course Objectives

What are the Course Objectives?

After completion of the data science with R Course at Naresh I technologies, you will be expertise and eligible for:

  • Complete knowledge of Data Science
  • Able to analyze big data
  • Able to work in Data Mining
  • Able to work on Statistic
  • Learn how to use different tool like Tableau, Map Reduce
  • Creation of Decision tree
  • Explore Big data concept

Who should go for this course

  • Any IT experienced Professional who are interested to build their career in Development/ Data Scientist.
  • Any B.E/ B.Tech/ BSC/ MCA/ M.Sc Computers/ M.Tech/ BCA/ BCom College Students in any stream.
  • Fresh Graduates.

Pre-requisites

The course can learn by any IT professional having basic knowledge of :

  • Mathematics
  • Statistic
  • Any Programming Language

Course Curriculum

  • What is R?
  • Why R?
  • Installing R
  • R environment
  • How to get help in R
  • R Studio Overview
  • 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
  • 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
  • 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
  • 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
  • While loop
  • If loop
  • For loop
  • Arithmetic operations
  • Box plot
  • Histogram
  • Pie graph
  • Line chart
  • Scatterplot
  • Developing graphs
  • Cover all the current trending packages for Graphs
  • Sentiment analysis with Machine learning
  • C 5.0
  • Support vector Machines
  • K Means
  • Random Forest
  • Naïve Bayes algorithm
  • Correlation
  • Linear Regression
  • Non Linear Regression
  • Predictive time series forecasting
  • K means clustering
  • P value
  • Find outlier
  • Neural Network
  • Error Measure
  • 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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