**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

**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 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.

**Who this course is for:**

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