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Introduction to R – Free Udemy Courses

Introduction to R – Free Udemy Courses

Learn the core fundamentals of the R language for interactive use as well as programming

What you’ll learn

Introduction to R – Free Udemy Courses

  • 90 videos (15+ hours)
  • To educate you on the fundamentals of R
  • 140+ exercise problems
  • To accelerate your learning of R through practice

Requirements

  • Windows/Mac/Linux

  • Basic proficiency in math – vectors, matrices, algebra

  • Basic proficiency in statistics – probability distributions, linear modeling, etc

  • A high-speed internet connection

Description



UPDATE



: As of Nov 22, 2018, this course is now free! Many thanks to all my existing students who made it possible for the wider audience to benefit from the course material ????

With “



Introduction to R



“, you will gain a solid grounding of the fundamentals of the R language!

This course has about



90 videos



and



140+ exercise questions



, over 10 chapters. To begin with, you will learn to



Download and Install R



(and R studio) on your computer. Then I show you some basic things in your first R session.

From there, you will review topics in increasing order of difficulty, starting with



Data/Object Types



and



Operations



,



Importing into R



, and



Loops and Conditions



.

Next, you will be introduced to the use of



R



in



Analytics



, where you will learn a little about each object type in R and use that in Data Mining/Analytical Operations.

After that, you will learn the use of R in



Statistics



, where you will see about using R to evaluate Descriptive Statistics, Probability Distributions, Hypothesis Testing, Linear Modeling, Generalized Linear Models, Non-Linear Regression, and Trees.

Following that, the next topic will be



Graphics



, where you will learn to create 2-dimensional Univariate and Multi-variate plots. You will also learn about formatting various parts of a plot, covering a range of topics like Plot Layout, Region, Points, Lines, Axes, Text, Color, and so on.

At that point, the course finishes off with two topics:



Exporting out of R



, and



Creating Functions



.

Each chapter is designed to teach you several concepts, and these have been grouped into sub-sections. A sub-section usually has the following:

  • A Concept Video
  • An Exercise Sheet
  • An Exercise Video (with answers)





Why take a course to learn R?

When I look to advancing my R knowledge today, I still face the same sort of situation as when I originally started to use R. Back when I was learning R, my approach was learning by doing. There was a lot of free material out there (and I refer to that early in the course) that gave me a framework, but the wording was highly technical. Even with the R help and the free material, it took me up to a couple of months of experimentation to gain a certain level of proficiency.



What I would have liked at that time was a way to learn the fundamentals more quicker



. I have designed this course with exactly that in mind.



Why my course?

For those of you that are new to R, this course will cover



enough breadth/depth in R



to give you a solid grounding. I use



simple language



to explain the concepts. Also, I give you 140+ exercise questions many of which are based on



real-world data



for practice to get you up and running quickly, all in a single package. This course is designed to get you functional with R in a



little over a week



.

For those beginners with some experience that have learned R through experimentation, this course is designed to complement what you know, and round out your understanding of the same.

Who this course is for:

  • Enterprise Data Analysts
  • Students
  • Anyone interested in Data Mining, Statistics, Data Visualization










If the links does not work, contact us we will fix them











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