Data Visualization with R Programming

Features Includes:
  • Self-paced with Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App

Course Preview Video


R is most popular and the leading open source language in data science and statistics. Today, R language is the choice for most data science professionals in every industry and academics.

This course is thoroughly described R programming, Visualization and Data Science for beginners using real life examples.

Let’s parse that.

  •  This course does not require a prior quantitative or mathematics background. It starts fundamental concepts of R programming, introducing basic concepts such as the mean, median etc and eventually covers all aspects of an analytics (or) data science career from analysing and preparing raw data to visualizing your findings
  • This course is an introduction to Data Science and Visualization using the R programming language
  • Real life examples: Every concept is explained with the help of examples, case studies and source code in R wherever necessary
  • Data Analysis with R: Datatype and Data structures in R, Vectors, Arrays, Matrices, Lists, Data Frames, Reading data from files, Aggregating, Sorting & Merging Data Frames
  • Learn how to plot using GGPLOT2

Basic knowledge
  • No prior knowledge of programming is required. Just a basic knowledge of computer applications is enough for this course

What will you learn
  • Learn R programming from scratch
  • Use of R Studio
  • Principles of programming
  • Concept of vectors in R
  • Create your own variable
  • Data types in R
  • Know the use of while() and for()
  • Build and use matrices in R
  • Use matrix() function, learn rbind() and cbind()
  • Install packages in R
  • Understand the Normal distribution
  • Practice working with statistical data in R
  • Add your own functions into apply statements
  • R functions
  • Create your own function
  • Use of If- Else Statement
  • Scatter plot
  • Box plot
  • Density plot
  • Histogram Plot
  • Pie chart
  • Plot With GGplot2
Course Curriculum
Number of Lectures: 44 Total Duration: 05:54:22

No Review Yet