Introduction to R

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Free Online Course: Introduction to R provided by Udemy is a comprehensive online course, which lasts for 15 hours worth of material. The course is taught in English and is free of charge. Introduction to R is taught by Jagannath Rajagopal.

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

    What you'll learn:

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

    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 learn 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 in nature. 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 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 little over a week.

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