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!
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 wellknown 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 opensource language.
This course will be constantly updated based on students feedback.
Installing R and R Studio
Introduction  Basic Operations in R

3Installing R
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/installingRwindowsmacubuntu

4Installing R Studio
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 userfriendly.
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/installrandrstudioonmace911606ce4f4

5Basic Questions about R
A test with some questions about the R install process.
Vectors and the Environment

6[Slides]  R as a Calculator and Vectors
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.

7Using R as a Calculator  Simple Calculations
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;

8Using R as a Calculator  Functions
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.

9R as a Calculator  Quiz
This exercise has some questions regarding the usage of RStudio and mathematical operations in R.

10Practical Exercises  Time to test your skills!

11Link to Exercise Solutions
R Data Types

12Creating Vectors and Knowing the Environment
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;

13Vector Indexing and Slicing
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;

14Calculations with Vectors
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;

15More Functions and Dealing with Unexpected Values
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.

16Comparison Operators
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;

17Vectors Names Property
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;

18Modifying Vector Elements

19Comparing R with Excel and SQL

20R Vectors and the Environment
The following questions will be based on the "vectors and environment" lectures. If you are having trouble understanding the logic behind the answers check the slides that are available in the beginning of the lecture and try to play around in R studio to understand the language behavior.

21[TUTORIAL]  Completing and Debugging Coding Exercises on Udemy Platform

22Vectors Coding Exercise

23Practical Exercises  Time to test your skills on Vectors!
R Arrays

24[Slides]  R Data Types

25Underlying Data Types and Types at the Class Level
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.

26Checking Data Types of Objects
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.

27Converting Data Types

28Introduction to Factors
In this lecture we will investigate a new data type: factors!

29Dealing with Dates

30R Data Types
This test will test your skills on R data types!

31R Data Types Coding Exercise

32Practical Exercises  Time to test your skills on Data Types!
R Matrices

33[Slides]  Arrays and Matrices

34Creating Arrays
In this lecture, we are going to get introduced to our first multidimensional object, the Array!

35Indexing and Modifying Arrays
In this lecture, we are going to manipulate Arrays and use index properties to access element!

36Array Operations
In this lecture we are going to learn how to modify multidimensional objects!

37Array Dimnames Property
In this lecture we are going to explore the dimnames property of arrays and check a few other properties.

38Combining Arrays
In this lecture we are going to learn the rbind and cbind commands to combine arrays!

39Arrays  Quiz
Test your understanding on arrays creation and indexing. If you are having trouble return to the videos to consolidate your knowledge!

40R Arrays  Coding Exercise

41Practical Exercises  Time to test your skills on Arrays!
Data Frames  Introduction

42Creating Matrices
In this lecture we are going to learn how to construct matrixes and check the similarities between matrixes and arrays!

43Matrix Operations

44Matrices  Quiz
Test your understanding on matrices. If you are having trouble return to the videos to consolidate your knowledge!

45R Matrices  Coding Exercise

46Practical Exercises  Time to test your skills on Matrices!
R Lists

47[Slides]  Data Frames & Lists

48Creating a Data Frame
In this lecture we will learn how to create this new object, the Data Frame!

49Indexing and Modifying Data Frames

50Expanding Data Frames
In this lecture we will learn how we can expand Data Frames with the cbind and rbind commands!

51Removing Elements from Data Frames
In this lecture we are going to learn how we can remove rows or columns from data frames.

52Data Frames Questions
Time to test you skills on data frames! In this test we are going to see some questions regarding data frames.

53R Data Frames  Coding Exercise
Course Break

54Creating Lists
In this lecture we are going to explore a new object in R  R Lists!

55List Indexing
In this lecture we are going to see examples on how we can index list elements.

56Changing and Adding elements to Lists

57Deleting List Elements

58Combining Lists

59Lists Questions
Time to test your skills! In this quiz you are going to test your knowledge on lists!

60R Lists  Coding Exercises

61Practical Exercises  Time to test your skills on Lists!
Libraries
Working with Data Frames
Loading External Data

66Introduction

67Inspecting Data Frames

68Filtering Data Frames

69Creating New Columns in a Data Frame

70Apply Family

71New Column with Sapply

72Aggregating and Sorting

73Merging Data Frames

74Extra  Merging Data Frames using a SQLLike Library

75Plotting Overview (Base R)

76GGPlot 2 Overview

77Working with Data Frames Questions
Let's test your knowledge on Data Frames!

78Working with Data Frames Coding Exercises

79Practical Exercises  Time to test your skills on manipulating Data Frames!