R Basics - R Programming Language Introduction
Learn the essentials of R Programming - R Beginner Level!
R Basics - R Programming Language Introduction udemy course free download:
What you'll learn:
You will learn how to navigate in the RStudio interface
Genuine Interest in statistical programming
Computer ready to run R and RStudio
NO prior knowledge in programming is required!
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?
Who this course is for:
- Students who need R for their courses
- Web developers who want to implement data analysis features in their webpage
- Everybody interested in statistics and data sciences
- Researchers who perform data analysis including graphs
- Professionals working in analytics or related fields