R Programming - R Language for Absolute Beginners
R Programming course suitable for everyone, no coding experience or a statistics background needed
R Programming course suitable for everyone, no coding experience or a statistics background needed
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.
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Creating Vectors and Knowing the Environment
492Vector Indexing and Slicing
389Calculations with Vectors
593 Xem trướcMore Functions and Dealing with Unexpected Values
658Comparison Operators
286Vectors Names Property
346Modifying Vector Elements
350Comparing R with Excel and SQL
277R Vectors and the Environment
[TUTORIAL] - Completing and Debugging Coding Exercises on Udemy Platform
500Vectors Coding Exercise
0Practical Exercises - Time to test your skills on Vectors!
[Slides] - R Data Types
259Underlying Data Types and Types at the Class Level
403Checking Data Types of Objects
268Converting Data Types
446Introduction to Factors
490Dealing with Dates
690R Data Types
R Data Types Coding Exercise
0Practical Exercises - Time to test your skills on Data Types!
Introduction
120Inspecting Data Frames
732Filtering Data Frames
852Creating New Columns in a Data Frame
445Apply Family
769New Column with Sapply
689Aggregating and Sorting
577Merging Data Frames
740Extra - Merging Data Frames using a SQL-Like Library
238Plotting Overview (Base R)
732GGPlot 2 Overview
429Working with Data Frames Questions
Working with Data Frames Coding Exercises
0Practical Exercises - Time to test your skills on manipulating Data Frames!
Introduction
166Loading the Data
225Extracting the Number of Rows
58Checking the First Rows
49Counting Rows by Store
87Converting to a Data Frame
83Extracting the Store with most Rows
143Summing up the Total Sales by Store
127Modifying Column Names
69Plotting Total Sales per Store
153Extracting the Mean of every Column
135Creating a New Column
202Plotting the Sales by Date for a Specific Store
424Using Ggplot to Enhance the Sales Plot
420Plotting the Sales By Date for Multiple Departments
769Reading the Crime Data Excel File
168Setting Column Names
98Building a Pipeline and Dropping Null Values
400Preparing Row Names
159Drop Columns
228Convert Data to Numeric
159Assigning Row Names
125Automating Column Selection
310Hardcoded Selection vs. Automated (Rule Based) Selection
147Aggregating Data and Bar Plotting
643Creating a Data Pipeline Exercise
Functions - Intro
724Functions - Arguments
322Functions - Control Flow - Loops
661Functions - Control Flow - If Statements
376Functions - Control Flow - While Loops
414Functions - Working with Data 1
583Functions - Working with Data 2
241Functions Questions
Coding Exercise - Functions and Vectors
0Coding Exercise - Functions 2
0Coding Exercise - Functions and DataFrames
0Computer with at least 4GB Ram
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
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