R Programming

R Programming, available at $19.99, with 65 lectures, and has 4 subscribers.

You will learn about Students will have a good working knowledge on R Programming and can use it for their Educational as well as Business projects and assignments. Working professionals can also benefit from this course as this course provides many tips and tricks which they can use it for their Corporate presentations. The topics that will be covered in this course are divided into 10 modules. Each module leads into the next and should be covered in order. This course is ideal for individuals who are This course is highly recommended for Students, Working Professionals, Business Analysts, Consultants, Businessmen, Teachers, Lecturers, Professors and data science enthusiasts. or The course is best for individuals who are in the field of Business Analytics or is eager to join the same It is particularly useful for This course is highly recommended for Students, Working Professionals, Business Analysts, Consultants, Businessmen, Teachers, Lecturers, Professors and data science enthusiasts. or The course is best for individuals who are in the field of Business Analytics or is eager to join the same.

Enroll now: R Programming

Summary

Title: R Programming

Price: $19.99

Number of Lectures: 65

Number of Published Lectures: 65

Number of Curriculum Items: 65

Number of Published Curriculum Objects: 65

Original Price: ₹799

Quality Status: approved

Status: Live

What You Will Learn

Students will have a good working knowledge on R Programming and can use it for their Educational as well as Business projects and assignments.
Working professionals can also benefit from this course as this course provides many tips and tricks which they can use it for their Corporate presentations.
The topics that will be covered in this course are divided into 10 modules.
Each module leads into the next and should be covered in order.

Who Should Attend

This course is highly recommended for Students, Working Professionals, Business Analysts, Consultants, Businessmen, Teachers, Lecturers, Professors and data science enthusiasts.
The course is best for individuals who are in the field of Business Analytics or is eager to join the same

Target Audiences

This course is highly recommended for Students, Working Professionals, Business Analysts, Consultants, Businessmen, Teachers, Lecturers, Professors and data science enthusiasts.
The course is best for individuals who are in the field of Business Analytics or is eager to join the same

There are people who are eager to move to Analytics careers but do not have the requisite skill sets. As we move into our 12th year in the Analytics Industry, OrangeTree Global has designed specific courses for freshers and working professionals who are looking at moving to Data Science, Machine Learning and Big Data Careers.

Since 2009, OrangeTree Global has embarked on an ambitious vision of providing affordable and effective Analytics Training and Education across the country.

OrangeTree Global has over a decade’s experience in upskilling professionals and helping them move to analytics jobs and careers within and outside India. If you are reading this, we hope to be a part of your journey too.

The following topics will be covered as part of this series. Each topic is described in detail with hands-on exercises done on R Studio to help students learn with ease. We will cover all the nitty-gritty that you need to know to get started with R along with the data manipulation, extraction, and visualization.

What is R?
Basic Operations in R
Data Types and Data structures in R
Subsetting in R
Additional Topics on Data Structures in R
Data Import and Export in R
Control Structures and User-Defined Functions in R
Data Visualization: Charting with R
Visualization on R using Google Vis
Visualization on R using GGPlot2

Course Curriculum

Chapter 1: What is R?

Lecture 1: Birth and Rise of R

Lecture 2: Installation Of R

Lecture 3: GUI of R

Lecture 4: R Studio Installation

Lecture 5: R Studio GUI

Chapter 2: Basic Operations in R

Lecture 1: Arithmetic Operations in R

Lecture 2: Expressions in R : Basic Idea

Lecture 3: Constant Values in R: Numeric and Non-Numeric

Lecture 4: Function Calls in R: Introduction to R Functions.

Lecture 5: Symbols and Assignment in R

Lecture 6: Keywords in R: NA, Inf, NaN, NULL, TRUE, FALSE

Lecture 7: Naming a Variable in R: Generally accepted conventions

Chapter 3: Control Structures and User Defined Functions in R

Lecture 1: Conditional Statements in R

Lecture 2: If statement in R: The Structure

Lecture 3: If Else statement in R: The Structure

Lecture 4: Ifelse() function in R

Lecture 5: Iteration in R

Lecture 6: The for loop in R

Lecture 7: The while loop in R

Lecture 8: The repeat statement in R

Lecture 9: lapply() function in R

Lecture 10: sapply() function in R

Lecture 11: apply() function

Lecture 12: User defined function in R

Lecture 13: Variable scooping in R: Global and Local Variables

Lecture 14: The plot function in R

Chapter 4: Data Visualization: Charting with R

Lecture 1: plot.window() function in R: Creating window

Lecture 2: points() function in R: Plotting points

Lecture 3: axis() function in R: Generating Axis

Lecture 4: box() function in R: Creating enclosure

Lecture 5: title() function in R: Assigning title

Lecture 6: par() function in R: Fixing plotting parameters

Lecture 7: lines() function in R: Adding connector lines

Lecture 8: Multi figure layout in R: Creating multiple charts in the same window

Lecture 9: hist() function in R: Plotting histograms

Lecture 10: Kernel Density Plot in R: The non-parametric probability distribution

Lecture 11: Comparing Groups via Kernel Density in R

Lecture 12: Simple Bar Plot in R: Visualizing categorical data

Lecture 13: Stacked Bar Plot in R: Understating category composition

Lecture 14: Grouped Bar Plot in R

Lecture 15: Line Charts in R

Lecture 16: Pie Charts in R

Lecture 17: Boxplot in R: Understanding data distributions and outliers

Lecture 18: Using Google Chart Tools with R (Package googleVis)

Lecture 19: Geo Charts in R basic example

Chapter 5: Visualization on R using Google Vis

Lecture 1: Introduction to the package GoogleVis in R

Lecture 2: Line chart using GoogleVis in R

Lecture 3: Bar chart and Column chart using GoogleVis in R

Lecture 4: Stepped chart and Combo chart using GoogleVis in R

Lecture 5: Bubble chart using GoogleVis in R

Lecture 6: Candle-stick Chart using GoogleVis in R

Lecture 7: Pie chart and Gauge chart using GoogleVis in R

Lecture 8: Geo charts using GoogleVis in R

Lecture 9: Annotation charts using GoogleVis in R

Lecture 10: Histogram using GoogleVis in R

Chapter 6: Visualization on R using GGPlot2

Lecture 1: Introduction and understanding the GGPLOT2 syntax in R

Lecture 2: Scatter Plot and Jitter Plot using GGPlot2 in R

Lecture 3: Counts chart using GGPlot2 in R

Lecture 4: Maginal Histogram/ Boxplot using GGPlot2 in R

Lecture 5: Correlogram using GGPlot2 in R

Lecture 6: Ordered Bar chart using GGPlot2 in R

Lecture 7: Histogram on continuous and categorical variable using GGPlot2 in R

Lecture 8: Density Plot and Box Plot using GGPlot2 in R

Lecture 9: Pie chart and Bar chart using GGPlot2 in R

Lecture 10: Spatial Map (an Overview) and Conclusion on the Tutorial

Instructors

OrangeTree Global
Analytics Trainer At OrangeTree Global.

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