Data Science Using R Programming 6weeks

DATA SCIENCE USING R PROGRAMMING 6 WEEKS TRAINING IN NOIDA

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This is a complete tutorial to learn data science and machine learning using R. By the end of this tutorial, you will have a good exposure to building predictive models using machine learning on your own.R is a free programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. R is an implementation of the S programming language combined with lexical scoping semantics inspired by Scheme.S was created by John Chambers while at Bell Labs. You can learn this technology from beginning to end in Ducat.To get quality training, you need to learn from trainers highly skilled in this technology. Professionals handling projects in real time will assist students and fresher's to understand challenges and working scenario in the industry. Ducat is the Best Data Science Using R Programming institute in noida.

STATISTICS in business world

Descriptive statistics
Inferential Statistics
Statistical data analysis
Variables
Sample and Population Distributions
Interquartile range
Central Tendency
Normal Distribution
Skewness.
Boxplot
Five Number Summary
Standard deviation
Standard Error
Hypothesis

Introduction to Data Analytics

Objectives:

This module introduces you to some of the important keywords in R like Business Intelligence, Business

Analytics, Data and Information. You can also learn how R can play an important role in solving complex analytical problems.
This module tells you what is R and how it is used by the giants like Google, Facebook, etc.
Also, you will learn use of 'R' in the industry, this module also helps you compare R with other software
in analytics, install R and its packages.

Topics

Business Analytics, Data, Information
Understanding Business Analytics and R
Compare R with other software in analytics
Install R
Perform basic operations in R using command line

R objects and Data types

Vector
Matrix
Array
Factor
List
Data Frame
Factors
NA/NAN
Explicit Coercion
Lists
Missing Value

Inbuilt Functions of R

Environment functions
Statistical Functions
li>Text Functions
Mathematical Functions
Reading Data from R
Writing Data into R
Files connection

Control Structure of R

If
For
Repeat
While
Next
Return

Writing Functions in R

Loop Function of R

Lappy
Tappy
Split
Mappy
Apply

Date and time in R

Dates in R
Time in R
Operation on Dates and Time on R

Basic Graphs in R

Creating a graph
Density Plot
Dot Plot
Bar Plot
Line Charts
Pie Charts
Box Plot
Scatter Plot
Histogram
Normal QQ Plot

Advance Graphs in R

Graphical Parameters
Lattice Graphs
Combining Plot
Ggplots Graph
Probability Graphs
Correlograms

PREDICTIVE MODELLING IN MARKETING

Personal loans cross selling
Life insurance
Regression
Variable selection
Multiple regression
Logistic regression
Multi-colinearity

BUSINESS ENVIRONMENT with DATA SCIENCE

To implement the statistical solutions that the team comes up with, sound programming and insight generation.
Communicate the insights using business-friendly presentations
Actionable insights
CORRELATION
Histogram, scatter plot, boxplot

PROJECTSDATA

SCIENCE CASE STUDIES

Facebook
Data science implementation by Indian authority
Fraud detection by RBI
RISK ANALYTICS
Dealer segmentation

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