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Are you interested in data science?
Do you want to learn R totally from scratch?
Are you looking for an easy step by step approach to get into R?
Do you want to take an easy R course for BEGINNERS?
Well, if your answer is YES to some of these questions, look no further, this course will help you.
I created this course for the total beginner. That means for you: No prior knowledge required! If this is your first computer programming language to use - congratulations, you found your entry level material. If you are new to data science, no problem, you will learn anything you need to to start out with R.
That also means for you: if you are already used to R, you will likely benefit more from an advanced course. I have more than ten intermediate and advanced R courses available on Udemy, which might be more suited towards your needs. Check out the r-tutorials instructor profile for more info.
Let’s take a look at the content and how the course is structured:
We will start with installation, the R and RStudio interface, add on packages, how to use the R exercise database and the R help tools.
Then we will learn various ways to import data, first coding steps including basic R functions, functions and loops and we will also take a look at the graphical tools.
The whole course should take approx. 3 to 5 hours, and there are exercises available for you to try out R. You will also get the code I am using for the demos.
Anything is ready for you to enter the world of statistical programming.
What R you waiting for?
Martin
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| Section 1: Introduction | |||
|---|---|---|---|
| Lecture 1 |
Welcome to R Basics
|
02:49 | |
| Lecture 2 |
Download R and RStudio
|
04:22 | |
| Lecture 3 |
RStudio Orientation
|
18:26 | |
| Lecture 4 |
Course Script
|
06:02 | |
| Lecture 5 |
The Structure of the R Ecosystem
|
14:33 | |
| Lecture 6 |
R Help Features
|
17:49 | |
| Lecture 7 |
Using R Functions
|
11:01 | |
| Lecture 8 |
Practice R - the R Exercise Database
|
02:39 | |
| Lecture 9 |
Three Common Mistakes of R Beginners
|
11:03 | |
| Section 2: Getting started with coding | |||
| Lecture 10 |
Your First Lines of R Code
|
14:38 | |
| Lecture 11 |
Using Some Basic Functions
|
12:59 | |
| Lecture 12 |
Exercise and Solution - Basic Coding
|
06:16 | |
| Lecture 13 | 06:39 | ||
In this video I will show you some basic examples of functions and loops in R. The Erathostenes loop was taken from the Level 1 course where you can find this as an exercise. |
|||
| Lecture 14 |
R Datasets and Data.Frames
|
09:26 | |
| Lecture 15 |
Importing CSV Files
|
06:04 | |
| Lecture 16 |
Advanced Data Import - Bonus Material from the Data Pre-Processing Course
|
07:53 | |
| Lecture 17 |
How to Best Structure Your R Learning Experience
|
12:38 | |
| Lecture 18 |
R Base Graphs
|
10:52 | |
| Lecture 19 |
R Base Graphs 2
|
15:41 | |
| Lecture 20 |
Exercise and Solution - R Base Graphs
|
03:10 | |
| Section 3: Bonus material from the other R-Tutorials courses | |||
| Lecture 21 | 05:13 | ||
Learn how to handle csv and similar files in R. csv is my favourite format when it comes to loading data frames into R. In this video I will show you how to download a zip data file from an external source and how to get it into R. You will also learn about working directories and how to save R scripts. |
|||
| Lecture 22 | 05:19 | ||
The apply family of functions is a way to do loops in R. Apply helps you to write shorter code and get results faster. Course: R Level 1 |
|||
| Lecture 23 | 06:29 | ||
The nortest package offers some very useful tests for normality. Along with some graphical tools you can determin if you have normal distributed data or not. Course: Statistics in R |
|||
| Lecture 24 | 03:31 | ||
The package lattice is quite useful for scientific publications. Lots of statistical papers contain lattice plots. In this video you will learn about some lattice plots. Course: Graphs in R |
|||
| Lecture 25 | 12:08 | ||
This is an example video of the course "Text mining, scraping and sentiment analysis in R". The is the solution to one of the exercises of the course. |
|||
| Lecture 26 |
Course Machine Learning: KNN Classification
|
05:51 | |
| Lecture 27 |
Course Machine Learning: Linear Discriminant Analysis
|
05:43 | |
| Lecture 28 |
Course Career Guide: Statistical Software Packages - Alternatives to R
|
13:15 | |
| Lecture 29 |
Where to get more info
|
00:36 | |
R-Tutorials is your provider of choice when it comes to analytics training courses! Try it out – our 30,000+ students love it.
We focus on Data Science tutorials. Offering several R courses for every skill level, we are Udemy's number one R training provider. On top of that courses on Tableau, Excel and a Data Science career guide are available.
All of our courses contain exercises to give you the opportunity to try out the material on your own. You will also get downloadable script pdfs to recap the lessons.
The courses are taught by our main instructor Martin – trained biostatistician and enthusiastic data scientist / R user.
Should you have any questions, you are invited to check out our website, you can open a discussion in the course or you can simply drop us a pm.
We are there to help you boost your career with analytics training – Just learn and enjoy.