Introduction to R

LEARN THE CORE FUNDAMENTALS OF THE R LANGUAGE FOR INTERACTIVE USE AS WELL AS PROGRAMMING


Course content:

Section 1: Introduction
Section 2: Your first R Session
Section 3: Basics - Objects and Data Types
Section 4: Importing Data into R
Section 5: Data Mining/Manipulation
Section 6: Loops and Conditions
Section 7: Statistics
Section 8: Graphics
Section 9: Exporting Data out of R
Section 10: Working with Functions
Section 11: Conclusion


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 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.



This course is for:

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

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

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