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R Programming - R Language for Absolute Beginners

Name: R Programming - R Language for Absolute Beginners
Rating: 4.6 (3544 reviews)

R Programming course suitable for everyone, no coding experience or a statistics background needed

Bestseller

Highest Rated

Created byIvo Bernardo

Last updated 1/2026

English

What you'll learn

Installing R and R Studio
Manipulating R Vectors, Arrays and Matrixes
Manipulating R Data Frames
Plotting Data Using R
Analyzing Real Datasets using R
Organizing your Code in R
Develop your own Functions in R
Summarizing Data with R
Load Excel Files with R
Compute Basic Statistics about a Dataset
Install External Libraries to Power up R
Aggregate and Sort Data
Subset Data

Coding Exercises

This course includes our updated coding exercises so you can practice your skills as you learn.

Course content

19 sections • 113 lectures • 10h 39m total length

Welcome!5:31
In this lecture we will get an overview on what we will learn in this course.
We will approach what I name the Learning Loop - discussing some strategies on how to approach the course material to improve the success rate of the students in this course.
Course Materials0:25

Installing R5:11
In this lecture we will set up R base on our Windows machines and make the first step in our R programming journey. You will learn to:
Install R;
Understand R interface for simple calculations;
Note: This tutorial is aimed at Windows users, to install on mac see: https://www.datacamp.com/community/tutorials/installing-R-windows-mac-ubuntu
Installing R Studio6:20
In this lecture, we will download our main software to program in R - RStudio. RStudio is probably the most famous GUI(Graphical User Interface) to program in R and is really user-friendly.

We will learn how to:
Install R Studio;

Note: This lecture is aimed at Windows users. See this blog post for instructions to install R Studio on a Mac: https://medium.com/@GalarnykMichael/install-r-and-rstudio-on-mac-e911606ce4f4
Basic Questions about R

[Slides] - R as a Calculator and Vectors14:14
Slides Lecture where we will explore some of the fundamental concepts about vectors and R environment.
In this lecture we will explore the concept of R objects such as vectors and talk a bit about how you can deal and interact with the R environment.
Using R as a Calculator - Simple Calculations5:11
In this lecture we will have our first exposure to coding in R Studio, using R as a calculator.

What you will learn:
Summing two numbers in R;
Subtracting two numbers in R;
Multiplying two numbers in R;
Dividing two numbers in R;
Operations order in R;
Using R as a Calculator - Functions4:33
In this lecture we will check how we can call mathematical functions in R Studio.
What you will learn:
Compute a square root of a number;
Compute a exponential of a number;
Compute a logarithm of a number;
Checking the ? command to access help on functions.
R as a Calculator - Quiz
Practical Exercises - Time to test your skills!0:14
Link to Exercise Solutions0:07

Creating Vectors and Knowing the Environment8:12
In this lecture we are going to create our first vector and understand some basic concepts of the R environment.
You will learn how to:
Create vectors with the command c();
Create objects in the environment;
Removing objects from the enviroment;
Understanding the data type of R objects;
Vector Indexing and Slicing6:29
In this Lecture we are going to understand three important concepts regarding indexing. You will learn how to do:
Numeric Indexing;
Slicing Indexing;
Multiple selection Indexing;
Calculations with Vectors9:53
In this lecture we are going to perform calculations with vectors. You will learn how to:
Sum vector elements;
Summing two vectors;
Multiplying two vectors;
Apply functions to vectors;
More Functions and Dealing with Unexpected Values10:58
In this lecture we will see some more functions that we can apply on vectors and explore further arguments of these functions.
You will learn how to:
Compute median, mean and standard deviation of a vector;
Sort vectors;
Extract the length of vectors;
Knowing how to deal with NA, NaN and Inf.
Comparison Operators4:46
In this lecture we are going to explore comparison operators. You will learn how to:
Use > and < operators;
Apply equality or inequality operators;
Use returning vectors from comparison operators as indexes;
Vectors Names Property5:46
In this lecture we are going to explore how we can label vector elements. You will learn how to:
Use the names property;
Index by name;
Powering up the which command;
Modifying Vector Elements5:50
Modify vector elements in R by assigning new values to specific positions, changing ranges and conditional replacements, extending length, and deleting elements with index negation.
Comparing R with Excel and SQL4:37
Explore how R handles vectors, performing mean, max, and variance calculations just like in Excel. Compare R with Excel and SQL, illustrating vector operations and column-based queries.
R Vectors and the Environment
[TUTORIAL] - Completing and Debugging Coding Exercises on Udemy Platform8:20
Learn how to complete and debug R coding exercises on the Udemy platform, including summing vectors, removing NA values, and using the solution folders to check and run code.
Vectors Coding Exercise
Practical Exercises - Time to test your skills on Vectors!1:15

[Slides] - R Data Types4:19
Underlying Data Types and Types at the Class Level6:43
In this lecture we will uinderstand the difference between underlying data types and class level data types - exploring the most common data types in R.
Checking Data Types of Objects4:28
In this lecture we are going to check the class of elements in vectors and also check how we can test the class of a variable in the environment.
Converting Data Types7:26
Introduction to Factors8:10
In this lecture we will investigate a new data type: factors!
Dealing with Dates11:30
Explore how to work with dates in R, convert strings to date objects with as.Date, handle date formats, and extract day, month, and year for time series analysis.
R Data Types
R Data Types Coding Exercise
Practical Exercises - Time to test your skills on Data Types!0:34

[Slides] - Arrays and Matrices6:17
Master arrays and matrices in R by creating multi-dimensional data with the array function and matrix constructor, then index and name dimensions to access elements.
Creating Arrays9:14
In this lecture, we are going to get introduced to our first multi-dimensional object, the Array!
Indexing and Modifying Arrays7:41
In this lecture, we are going to manipulate Arrays and use index properties to access element!
Array Operations6:10
In this lecture we are going to learn how to modify multi-dimensional objects!
Array Dimnames Property9:24
In this lecture we are going to explore the dimnames property of arrays and check a few other properties.
Combining Arrays3:36
In this lecture we are going to learn the rbind and cbind commands to combine arrays!
Arrays - Quiz
R Arrays - Coding Exercise
Practical Exercises - Time to test your skills on Arrays!1:23

Creating Matrices6:19
In this lecture we are going to learn how to construct matrixes and check the similarities between matrixes and arrays!
Matrix Operations10:04
Create and manipulate matrices in R through element-wise operations and dimension checks. Practice dot product multiplication using % and understand inner and outer dimensions to avoid non conformable arrays errors.
Matrices - Quiz
R Matrices - Coding Exercise
Practical Exercises - Time to test your skills on Matrices!0:41

[Slides] - Data Frames & Lists13:25
Learn how data frames and lists enable multi-type data in R, with data frames as two-dimensional tables akin to Excel, and lists as flexible containers.
Creating a Data Frame9:19
In this lecture we will learn how to create this new object, the Data Frame!
Indexing and Modifying Data Frames2:55
Expanding Data Frames4:33
In this lecture we will learn how we can expand Data Frames with the cbind and rbind commands!
Removing Elements from Data Frames2:54
In this lecture we are going to learn how we can remove rows or columns from data frames.
Data Frames Questions
R Data Frames - Coding Exercise

Creating Lists8:44
In this lecture we are going to explore a new object in R - R Lists!
List Indexing7:32
In this lecture we are going to see examples on how we can index list elements.
Changing and Adding elements to Lists5:05
Deleting List Elements2:53
Learn how to remove elements from an R list by assigning null, compare double bracket and single bracket indexing, and see why dollar notation needs named elements.
Combining Lists3:46
Lists Questions
R Lists - Coding Exercises
Practical Exercises - Time to test your skills on Lists!0:53

Requirements

Computer with at least 4GB Ram

Description

So, you've decided that you want to learn R or you want to get familiar with it, but don't know where to start? Or are you a data/business analyst or data scientist that wants to have a smooth transition into R programming?

Then, this course was designed just for you!

Hear what other students have to say first:

"I came to this course after an online university course *cough coursera cough* left me crying. The entire curriculum that this class covers was what they covered in week 1, and from what I've heard, R has a very steep learning curve. The extra time taken to even walkthrough installation is clearer here. It is much appreciated. You get lots of opportunities to practice, follow along, and really build your knowledge step by step." 5 star review by a Udemy user

"A really really good course for beginners in R, highly recommended. Everything is well explained in detail and enough coding exercises to get you familiarize with concepts before moving to the next section.

Thanks for this Ivo, appreciated." 5 star review by a Udemy user

"Easy to understand, calm and clear explanation. Covered points which are ignored by other tutors. Great" 5 star review by a Udemy user

This course was designed to be your first step into the R programming world! We will delve deeper into the concepts of R objects, understand the R user interface and play around with several datasets. This course contains lectures around the following groups:

Introductory slides lectures with the most well-known commands for each type of R object.
Code along lectures where you will see how we can implement the stuff we will learn!
Test your knowledge with questions and practical exercises with different levels of difficulty!
Analyze real datasets and understand the thought process from question to R code solution!

This course was designed to be focused on the practical side of coding in R - instead of teaching you every function and method out there, I'll show you how you can read questions and examples and get to the answer by yourself, compounding your knowledge on the different R objects.

At the end of the course you should be able to use R to analyze your own datasets. Along the way you will also learn what R vectors, arrays, matrixes and lists are and how you can combine the knowledge of those objects to power up your analysis.

Here are some examples of things you will be able to do after finishing the course:

Load CSV and Excel files into R;
Do interesting line plots that enable you to draw conclusions from data.
Plot histograms of numerical data.
Create your own functions that will enable you to reutilize code.
Slice and dice Data Frames, subsetting data for specific domains.

Join thousands of professionals and students in this R journey and discover the amazing power of this statistical open-source language.

This course will be constantly updated based on students feedback.

Who this course is for:

Data Analysts
Business Analysts
Financial Managers
Statisticians
Researchers
Software Engineering Undergraduates
Data Scientists
Data Engineers
R learners
Entry-level Data Scientists

R Programming - R Language for Absolute Beginners

What you'll learn

Explore related topics

Coding Exercises

Course content

Course Intro2 lectures • 6min

Installing R and R Studio2 lectures • 12min

Introduction - Basic Operations in R5 lectures • 24min

Vectors and the Environment10 lectures • 1hr 6min

R Data Types7 lectures • 43min

R Arrays7 lectures • 44min

R Matrices3 lectures • 17min

Data Frames - Introduction5 lectures • 33min

R Lists6 lectures • 29min

Course Break1 lecture • 2min

Requirements

Description

Who this course is for: