R Programming 2023- Hands on R Programming for Beginners
- Development
- May 09, 2025

R Programming 2023: Hands on R Programming for Beginners, available at Free, has an average rating of 3.45, with 19 lectures, 1 quizzes, based on 131 reviews, and has 6632 subscribers.
Free Enroll NowYou will learn about 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 basics of Data Science This course is ideal for individuals who are This course is for everyone, right from college students using R for a project to statisticians, programmers from other platforms, or pure beginners without any prior programming experience who want to become data analysts or data scientists It is particularly useful for This course is for everyone, right from college students using R for a project to statisticians, programmers from other platforms, or pure beginners without any prior programming experience who want to become data analysts or data scientists.
Enroll now: R Programming 2023: Hands on R Programming for Beginners
Summary
Title: R Programming 2023: Hands on R Programming for Beginners
Price: Free
Average Rating: 3.45
Number of Lectures: 19
Number of Quizzes: 1
Number of Published Lectures: 19
Number of Published Quizzes: 1
Number of Curriculum Items: 23
Number of Published Curriculum Objects: 23
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
R Programming 2023: Learn Basics of R Programming and gain one of employer’s most requested skills in 2023!
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 everyday, it calls for very unique skillsets 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 learning R Programming, with R Studio an IDE for R Programming, with a console, syntax editor for executing R Programming 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 would be able to understand and apply 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 aimed at
– Beginners who have no coding background in R Programming or otherwise
– Aspiring as well as professional data analysts, statisticians and programmers who want to pick up skills in R Programming
Course Curriculum
Chapter 1: Getting started with R!
Lecture 1: Setting up R and R Studio
Lecture 2: Understanding R Studio: Layout and Features
Lecture 3: Learn how to Import Files
Lecture 4: Updating Libraries
Chapter 2: Fundamentals of Programming
Lecture 1: Data Types and Data Structures
Lecture 2: Conditional Operators: If-else and Nested if-else if-else statements
Lecture 3: Logical Operators: AND, OR and NOT
Lecture 4: Build and Break For and While Loops!
Chapter 3: Data Structures in R
Lecture 1: Vectors: Character, Numeric, Complex and Logical
Lecture 2: Going through Vector Operations
Lecture 3: Word Game: Transforming words to Pig Latin
Lecture 4: More Vector functions: any(), rep() and all()
Lecture 5: Working with Films using Lists
Lecture 6: Matrices
Lecture 7: Preparing Class Report with a Matrix
Lecture 8: Introduction to Data-Frames
Lecture 9: Exploring more about Data-Frames
Lecture 10: Working with MT Cars Dataset
Chapter 4: Bonus Section: Visualizing data!
Lecture 1: Scatter and Line Plots
Instructors

Prashanth Chidambaram
Data Scientist | Supply Chain Analytics | Educator
Rating Distribution
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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