R Programming - Data Science using R
3.8 (70 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
8,115 students enrolled

R Programming - Data Science using R

Through this training you are going to learn the basics of R and how it can be used for data processing and data visuali
3.8 (70 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
8,115 students enrolled
Last updated 2/2019
English
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Current price: $83.99 Original price: $119.99 Discount: 30% off
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This course includes
  • 7 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • R is a programming language and related to software environment for statistical computing and graphics.
Course content
Expand all 62 lectures 06:46:52
+ R Programming - Practical Data Science Using R
26 lectures 03:42:27
How to use R Studio Continues
09:16
R Studio Basics
01:45
Basic Data Type R
09:24
More on Vector
09:16
Matrix
10:12
Matrix Continues
09:01
What is List
09:33
What is List Continues
05:28
Data Frame in R
09:22
Data Frame in R Sub Clip
04:57
Decision Making
10:35
Conditional Statements
12:22
Loops in R
09:53
While Loop
07:23
Break Statement
11:37
Functions
11:36
Alternative Loops
08:28
Alternative Loops Continue
09:05
User Define Function
09:11
Power of GGPLOT
03:09
GGPLOT 2 Visuals
08:51
Use of Function
10:29
+ Statistics Essentials for Analytics - Beginners
20 lectures 01:41:40
Introduction to Elements of Statistics
07:26
Random Numbers in Excel
05:00
Variables and Types of Variables
02:00
Quantitative and Qualitative
06:44
Understanding Ordinal Scale
05:07
Different Graphical Techniques
02:48
Examples on Graphical Representation
04:21
Bar Chart using R Software
05:50
Pie Chart using R Software
02:26
Entering Values to Variables
02:33
Illustration on Using Box Plot
09:22
Histogram Bar Graph
06:25
Examples on Histogram using R
04:57
Plotting the Scatter Plot
05:34
Different types of Sampling Techniques
02:36
Drawing Sample in R
05:12
Different Types of Sampling Technique
02:52
Different Types of Sampling Technique Continue
08:50
Probability Sampling
05:32
Non-Probability Sampling
06:05
+ Market Basket Analysis in R
8 lectures 39:00
Introduction to Market Basket Analysis in R
03:53
What is MBA
07:19
What is Basket
06:38
What Market Analysis is not
06:24
Element of MBA and Key Terminologies
01:58
Element of MBA and Key Terminologies Continues
04:16
Understanding Confidence And Support
06:02
Examples of Understanding Confidence and Support
02:30
+ Data Visualization with R Shiny - The Fundamentals
8 lectures 43:45
Introduction to Building Shiny Apps
02:49
Creating an Empty Shiny App
04:49
Shiny Web Application
01:54
Data and Resources
04:26
Adding Plain Text
06:09
Adding Inputs to the UI
06:37
Adding Elements to UI
06:00
Building an Output
11:01
Requirements
  • Passion to learn about R Programming Courses
  • Computer ready to run R and RStudio
  • Basic knowledge of statistics
  • Computer with Internet Connection
Description

Beginners Training on R Programming

R is a programming language and related to software environment for statistical computing and graphics. R programming languages is mostly used in graphics, it also used mostly by statisticians for developing software’s. Through this course one will be learning about basic R functions, special numerical values, array and matrix, repository and packages, installing a package, how to calculate variance, co-variance, cumulative frequency, learn about statistics, probability and distribution, random examples, discrete example and many as such concept about R.

Through this training you are going to learn the basics of R and how it can be used for data processing and data visualization to carry out exploratory analysis.

Target Customers:

  • Analytics professional

  • Anyone interested in R Programming related Training

  • Web developers

  • People interested in statistics and data sciences

  • Researchers

Pre-Requisites:

  • Passion to learn about R Programming Courses

  • Computer ready to run R and RStudio

  • Basic knowledge of statistics

  • Computer with Internet Connection

Statistics Essentials for Analytics – Beginners:

Data and analytics is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.

Through this tutorial you are going to learn the basic statistical concepts that are important to data analytics and its application using R, SPSS and Minitab.

The training will include the following;

  • Module1: Introduction to basic elements of Statistics

  • Module2: Measures of central tendency using R or Minitab Software

  • Module3: Measure of Dispersion using R/Minitab Software

  • Module4: Correlation and Simple linear regression using R programme

  • Module5: Understanding of Normal Distribution using R programme

Market Basket Analysis in R:

Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. We are understanding the conceptual foundations of association analysis and perform market basket analyses.
The training includes the following topics;

1. What is Market Basket analysis
– Introduction
– What Market Basket Analysis is not
– Elements of MBA and key terminologies
– Understanding Confidence and Support
– Association rules
– Examples of MBA
– Applications

2. Case study – MBA for marketing campaign using R
– Problem statement
– Introduction to apriori algorithm in R
– Deciding the support and confidence cutoffs
– Executing MBA
– Visualizing the results in R

Data Visualization with R Shiny – Basic Tutorials:

Data visualization is understanding the significance of data by placing it in a visual context. Patterns, trends that might go unnoticed in text-based data can be exposed and recognized easier with data visualization software. It basically involves presentation of data in a pictorial or graphical format.

Through this training we are going to learn how to use R and Shiny to create fascinating data visualizations.

The training will include the following;

  • Introduction

  • Web Development

  • Shiny

  • Resources

  • Getting Started

  • Structure of a Shiny App

  • UI

  • Server

  • Reactive Programming

  • Add-on Packages

Who this course is for:
  • Analytics professional
  • Anyone interested in R Programming related Training
  • Web developers
  • People interested in statistics and data sciences
  • Researchers