Free R Programming Course with Certificate

Introduction to R

Learn the fundamentals of R programming language with Introduction to R course. Discover the power of statistical computing, data analysis, and visualization using R. Enroll today!

Instructor:

Mr. Bharani Akella
4.57
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Beginner

Level

1.5 Hrs

Learning hours

161.9K+
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Skills you’ll Learn

About this Course

Introduction to R

Introduction to R is a beginner-level course designed to teach the fundamentals of R programming language. R is a popular open-source programming language used for statistical computing, data analysis, and visualization. It provides a wide range of statistical and graphical techniques, making it one of the most widely used languages for data analysis and research.
 

R is used by a variety of industries, including finance, healthcare, marketing, and education. It is commonly used for statistical analysis, predictive modeling, and data visualization. R's popularity is due to its versatility and flexibility, making it suitable for a wide range of applications.

 

Benefits of taking this course
 

  • In this course, you will learn the basics of R programming language, including variables, data types, data structures, control structures, functions, and packages. You will also learn how to use R for data analysis and visualization, including importing data, manipulating data, creating graphics, and performing statistical analysis.
  • The course is suitable for anyone who wants to learn R programming, including beginners and those with some programming experience. The course is taught by experienced instructors who deeply understand R and its applications. They will provide you with hands-on exercises and real-world examples to help you apply what you have learned.
  • By taking up this course, you can learn how to use R for a variety of tasks, including data cleaning and wrangling, exploratory data analysis, statistical modeling, and predictive analytics. You can also learn how to create visualizations such as scatter plots, histograms, box plots, and heat maps.
     

Some real-time examples of R usage are sentiment analysis of social media data, predicting customer churn for a telecom company, predicting stock prices, and building recommendation systems for e-commerce websites.
 

In conclusion, Introduction to R is valuable for anyone interested in learning R programming language. It provides a strong foundation in R programming, statistical computing, and data analysis, making it suitable for anyone interested in data analysis, research, or data science. With the skills you learn in this course, you can open up new career opportunities in data analysis and research. So, enroll in the Introduction to R course today and start your journey toward becoming a proficient R programmer.
 

Are you seeking more advanced data handling skills and getting valuable insights? The Great Learning’s Best Data Science Programs are for you. Enroll in the paid programs to gain career transitioning skills and course completion certificates.

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Course Outline

Installing R and Variables in R

Installation is the very first step of using the software. This module provides information to all the learners from where we have to install R and how to declare and initialize variables in R.

Data Types in R

Just like any other programing language R also has a variety of Data Types like numeric Data Type, Character Data Type, etc. In this module, we have a detailed discussion of Data Types in R with examples.

Operators in R

In this module, you will understand the types of Operators in R. you will learn about assignment operators, arithmetic operators, relational operators, and logical operators with suitable code examples.

Vector in R

This module equips you with the vector details in R, and you will also have a hands-on session on creating vector with appropriate code examples.

List in R

In R, a list is a generic object that represents an ordered collection of things. You will go through a detailed explanation on lists with code examples.

Matrix in R

A matrix is a rectangular array of numbers arranged in columns and rows. This module explains matrix- two dimensional data structure better with code examples.

Arrays in R

Arrays are important data storage structures with a specific number of dimensions. Through this module, you will learn about multidimensional homogeneous data structure- array in R with relevant code examples.

Factor and Dataframe in R

This module begins with explaining what a factor is and will help you understand it through an example. The second part of this section talks about what dataframes are and why they are essential. You will then work with sample codes to understand dataframes better.

Inbuilt Functions and Flow Control Statements in R

This module contains a hands-on session in R where you will thoroughly learn about inbuilt functions and flow control statements in R through informative code examples.

Our course instructor

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Mr. Bharani Akella

Data Scientist

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3.2M+ Learners
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82 Courses
Bharani has been working in the field of data science for the last 2 years. He has expertise in languages such as Python, R and Java. He also has expertise in the field of deep learning and has worked with deep learning frameworks such as Keras and TensorFlow. He has been in the technical content side from last 2 years and has taught numerous classes with respect to data science.

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Introduction to R

1.5 Learning Hours . Beginner

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