R for Data Science- Learn R Programming in 2 Hours
- Development
- May 01, 2025

R for Data Science: Learn R Programming in 2 Hours, available at $59.99, has an average rating of 4.25, with 35 lectures, based on 236 reviews, and has 3913 subscribers.
You will learn about Master all the basics of R Programming Learn basic concepts of Data Science Learn how to learn programming by yourself. Develop problem solving ability Pass their exams related to R This course is ideal for individuals who are Beginners entering the world of Data Science and R or Someone with experience in other languages but want to learn R or Someone with no programming experience looking to learn their first language. It is particularly useful for Beginners entering the world of Data Science and R or Someone with experience in other languages but want to learn R or Someone with no programming experience looking to learn their first language.
Enroll now: R for Data Science: Learn R Programming in 2 Hours
Summary
Title: R for Data Science: Learn R Programming in 2 Hours
Price: $59.99
Average Rating: 4.25
Number of Lectures: 35
Number of Published Lectures: 35
Number of Curriculum Items: 36
Number of Published Curriculum Objects: 36
Original Price: $89.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
BEST R BEGINNERS COURSE ON UDEMY!
LEARN R PROGRAMMING IN 2 HOURS!
This course will not waste your time, Are you tired of watching tutorials that take hours to explain simple concepts? You came to the right place. All this course asks you is 2-3 hours of your life.
Are you tired of taking countless courses on Udemy that are 10+ hours and you leave it halfway because they’re too darn long? You’ve come to the right place.
R for Data Science; LEARN R PROGRAMMING IN 2 HOURS? Sounds a bit too good to be true? No. This is the class I wish I had when I was trying to learn R Programming. I have a unique way of teaching, as I know how it must be overwhelming to learn a very complex programming language. The best part of this course is No prior programming experience is required.
2-3 hours is all you need to learn the basics of any programming language. Don’t believe me? just go check the reviews on my other courses. I’ve been teaching programming on Udemy for the last 4 years with similar short courses and my students love them.
So spend the next 2 hours that you would normally waste on a random Youtube video on this course and get maximum value in the minimum amount of time.
This course will introduce you to the concepts of R programming and Data Science in just 2 Hours.
Here’s What People Are Saying About My Programming Courses:
“Excellent Course. Worth every Dollar.
I always wanted to learn python. A few months back I purchased Ajay’s C++ course and I loved it. I was excited to see him release a course on python. The course doesn’t deviate from the topic like most courses on Python. This course didn’t disappoint at all. I am only halfway in the course, but I am still able to write small programs. Downloadable lecture notes make the learning process a lot easier. If you are a beginner like me and want to write fun programs on Python fast, look no further and enroll this course”
“Perfect Course for Beginners at Wonderful Price.
Well, I was a little concerned about enrolling in this course as it was just released, but I have to say it beats all the other C++ Courses in the market. The best part is that it’s just 2 hours, the content is straight forward and doesn’t waste your time just as it’s said in the promo video. Worth every buck! Will recommend it to all the beginners.”
“Very Good Course for Beginners
This course covers all the basic concepts of C++ in an easily understandable and interactive way. The instructor Ajay is also very helpful and replies readily to your queries and doubts. Overall I would strongly recommend this course to you if you are looking for basic knowledge of C++.”
“Excellent Course
I really enjoyed taking this course. I would definitely recommend this course to anyone with an interest in C++. It covers all the basics and good tips are given during the course. Ajay certainly knows the subject he teaches here. Looking forward to his next course.”
“Good primer
I’m brand new to Python, so this course was really just what I needed. I would like it to have been a bit longer and go a bit deeper, but as a brand new Python coder, I really enjoyed it and learned the basics.”
SO WHAT ARE YOU WAITING FOR? ENROLL NOW AND LET’S GET STARTED,
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: R Basics
Lecture 1: Data Types in R
Lecture 2: Making Use of R Data Types
Lecture 3: Introduction to Data Structures in R
Chapter 3: R Data Structures
Lecture 1: Introduction to Vectors in R
Lecture 2: Creating Vectors in R
Lecture 3: Coding in R Studio : Creating Vectors
Lecture 4: Operators in R
Lecture 5: Accessing Vector Elements in R
Lecture 6: Creating A Matrix in R
Lecture 7: Accessing Matrix Elements in R
Lecture 8: Data Frames in R
Lecture 9: Accessing Data Frames in R
Lecture 10: Introduction to Arrays in R
Lecture 11: Accessing Arrays in R
Lecture 12: Lists in R
Lecture 13: Factors in R
Lecture 14: Assignment Operator
Chapter 4: Practical Data Science using R : 1.Data Preparation
Lecture 1: Introduction to Practical Data Science
Lecture 2: Data Preparation in R Part 1: Importing Dataset
Lecture 3: Importing Datafiles (Additional Tip)
Lecture 4: Data Preparation in R Part 2: Dimensions and Column Names
Lecture 5: Data Preparation in R Part 3: Finding Missing Values
Lecture 6: Data Preparation in R Part 4: Fixing the Missing Values Problem
Chapter 5: Practical Data Science using R: 2.Visualization
Lecture 1: Visualization in R Part 1: Setting up the Environment,
Lecture 2: Visualization in R Part 2: Dot Plots or Scatter Plots
Lecture 3: Visualization in R Part 3: Bar Plots
Lecture 4: Visualization in R Part 4: Box Plots
Lecture 5: Visualization in R Part 4: Histograms and More.
Chapter 6: Practical Data Science using R : 3.Machine Learning
Lecture 1: Machine Learning using R Part 1: Introduction to Machine Learning.
Lecture 2: Machine Learning using R Part 2: What Will We Make?
Lecture 3: Machine Learning using R Part 3: Linear Regression without too much Math
Lecture 4: OPTIONAL : Machine Learning using R Part 3: Linear Regression with Math
Lecture 5: Machine Learning using R Part 3: Creating the Machine Learning Model in R
Lecture 6: Bidding Farewell! and to NEW BEGINNINGS.
Instructors

Ajay Warrier
Making Your Life Easier.
Rating Distribution
Frequently Asked Questions
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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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