Data Science with R course
Data Science with R course focuses on imparting indepth knowledge of various techniques for data analytics using R. The course includes reallife projects, case studies, and includes R CloudLabs for practice You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various packages available in R. As a part of the course, you will be required to execute reallife projects.
Data Science with R

This course will expose you to the data analytics practises executed in business world with :

Explanation of each concept in detail.

Real time projects

Assignments.

Scenario based discussions

Installation

Interview discussion and preparation


We will explore key areas as the analytical process.
How data is created, stored, accessed and processed and virtualized effectively as data scientist.

What you learn in this course will give you solid foundation in all the areas of analytics and help you to better position yourself for success within organization.

Our course will provide you detail understanding of complex quantitative and mathematical calculations.
Provide detail understanding of calcuations like mean,median, etc.
And help you in preparing virtualize data from raw data available.

Couse covers all the statistical calculations as well as practical calculations using Data science with R and Python.

If you are new to the R and Python.
Dont worry,our course will make you expert in data science with R and Python.

You can be expert to make automation,create desktop based applications or web applications or you can make use of your python skills in machine learning.

Our course will provide you the advance techniques of real world and data science tricks.

Course will help you to solve complex algorithms with easy few lines of code.

Target audience:

Engineering/Management/Post Graduate/Fresher students who want to boom there career with data science as Data Scientist or Data Analyst.

Data scientist who want single engine for analysing data and virtualizing it effectively.

Professionals who used to work with Excel and want to your R for statistical analysis.


Data Science The Big Picture

What is Data Science

Importance of Data Science

Data Science as a strategic asset

How organizations are using Data Science

What is Data Analysis

Types of Data and Business Analytics

Descriptive Analytics

Predictive Analytics

Prescriptive Analytics

Supply chain Analytics

Health chain Analytics

Marketing Analytics

Human Resource Analytics

Data Management and business analytics

Types of data sets and Data Models

Web Analytics and Business Intelligence

Course Content For R

Understanding R

Understanding Comprehensive R Archive Network (CRAN)

Which companies use R

R Installation on Windows/Linux/Mac

R Packages: Installation and practice

Studying operators (Arithmetic, Relational,Logical and Assignment Operators)

Statements and conditional statements in R

Break and Next statement

if else()

switch function

scan()

Loops in R

How to run R and batch script

Commonly used R functions

Defining data structure in R

Types of Data structures

Elements : Vectors, Matrix, Array

File operations with R

How to imort files in R

How to import an excel file

How to import minitab file

Importing csv files

Importing data from SQL databases

Types of apply functions: Lapply,Sapply,Tapply,Mapply functions

Managing data with R

Measuring the central tendency

Exploring relationship between variables

Visualizing relationships Scatter plots

Normal Distribution

Distance measures

Cosine

R Data structures: Vectors,Factors,Lists,Data Frames,Matrixes,Arrays

Exploring numeric variables

R packages to read,process and visualizer data

Understand linear regression and use it confidently to build models

Understand in detail for all data structure in R

Use linear regression in R to overcome difficulties of LINEST() in excel

Use descriptive statistics to perform quick study if data

Implement complex algorithms like Page Rank or Musical Recommendations

Introduction to regression

Linear regression

A regression case study : The Capital Asset Pricing Model (CAPM)

Linear regression in Excel

Linear regression in Excel: Preparing the data

Linear regression in Excel : Using LINEST()

Linear regression in R

Linear regression in R : lm() amd summary()

Multiple Linear Regression

Linear regression in R : Preparing the data

Adding categorical variables to a linear model

Robust regression in R: rlm()

Parsing regression Diagnostic plots

Non linear regression models

Data virtualization using R

The plot() in R

Drawing barplots

Control color pallatttes with Rcolorbrewer

Drawing Heat map

Drawing a scatterplot matrix

Plot a line with ggplot2

Introduction To Data Sets And Machine Learning

Data preparation for modelling

Machine learning techniques,features,models and design in R

Machine learning common use cases

Clustering

Study clustering and classification

Kmeans clustering using R

Distance measure types

Cosine measures

Implementing machine learning algorithms on larger data sets

Choosing machine learning algorithm with R

Thinking about the input data

Understanding of neural network

Network topology

Recurrent Gaussian Neural Network