R Programming Course for Beginners
Learn Programming in R and R Studio. Data Analytics. Data Science. Data Visualization. Packages: GGPlot2, Dplyr, StringR
Development ,Data Science,R Programming
Lectures -23
Resources -17
Duration -2.5 hours
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Course Description
R For Beginners: Learn the Basics of R Programming and gain one of the employer's most requested skills !!
Data Science is all about using data to solve some of society's most pressing problems. Harvard Business Review touted Data Science as the sexiest job of the 21st century, and no wonder Data Science is considered the future! With zettabytes and yottabytes of structured and unstructured data floating every day, it calls for very unique skills to uncover hidden patterns and generate valuable insights from data.
This course covers the basics of R/ R Studio Programming and several practical exercises relating to data science such as data analysis, building algorithms, generating insights and data visualization.
R Programming is often associated with having a very steep learning curve and many students give up feeling overwhelmed by the language. The 'R for Beginners' course follows a step-by-step approach, combining conceptual learning with hands-on assignments, quizzes and real-world projects.
Moreover, we would be learning R Programming, with R Studio an IDE for R Programming, with a console, and syntax editor for executing R code and debugging, as well as advanced tools for data visualization such as plots and maps.
At the end of this R/R Studio Programming course, you will be able to understand and apply the basics of R/R Studio programming, analyze large data sets, export your findings onto Excel, visualize data and even build your own algorithms!
Who is this course for?
- Beginners who have no coding background in R Programming or otherwise.
- Aspiring as well as professional data analysts, statisticians and programmers.
Goals
- Basics of R Programming.
- Learn to work with R and R Studio IDE.
- Build algorithms using logical and conditional operators as well as loop statements.
- Analyze large data-sets, and reproduce results in R/Excel.
- Thoroughly understand data structures in R and apply them as appropriate.
- Good working knowledge of stringr and dplyr packages.
- Understand the basics of Data Science.
Prerequisites
- R and R Studio.
- PC with Windows/Mac OS.
- Internet Connection.
- MS Office Excel.

Curriculum
Check out the detailed breakdown of what’s inside the course
Getting started with R!
4 Lectures
-
Setting up R and R Studio 02:00 02:00
-
Understanding R Studio: Layout and Features 03:09 03:09
-
Learn how to Import Files 05:03 05:03
-
Updating Libraries 02:04 02:04
Fundamentals of Programming
4 Lectures

Data Structures in R
10 Lectures

In Class Exercises
3 Lectures

Bonus Section: Visualizing Data!
1 Lectures

Instructor Details

Prashanth Chidambaram
Prashanth Chidambaram has a Bachelors in Chemical Engineering , MBA in Finance and Operations as well as an Associate's Degree in Piano.
Currently he works as a supply chain analyst and has worked on projects spanning network design and optimization, inventory planning, demand forecasting and has helped clients accelerate their digital journey.
As an educator, he runs an education services firm that provides music lessons to K-12 as well as pre-school students.
Feel free to contact him for more information on online classes, guidance, as well as for new courses.
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