Introduction to R
- Basic proficiency in math - vectors, matrices, algebra
- Basic proficiency in statistics - probability distributions, linear modeling, etc
- A high speed internet connection
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.
- Enterprise Data Analysts
- Anyone interested in Data Mining, Statistics, Data Visualization
- Introduction to R
- Course Logistics
- Section 1: Material
- Finding your way around R
- Exercise Answers - Finding your way around R
- Basic Commands
- Exercise Answers - Basic Commands
- Exercise Answers - Operators
- Exercise Answers - Miscellaneous
- Intro to R Studio
- Section 2: Material
- Data Types
- Exercise Answers - Data Types
- Object Types
- Exercise Answers - Object Types
- Exercise Answers - Vectors
- Arrays and Matrices
- Exercise Answers - Arrays and Matrices
- Factors and Lists
- Exercise Answers - Factors and Lists
- Data Frames and Tables
- Exercise Answers - Data Frames and Tables
- Section 3: Material
- Text Files
- Exercise Answers - Text Files
- Spreadsheets - Excel Files
- Exercise Answers - Excel Files
- Section 4: Material
- Vector Operations
- Exercise Answers - Vector Operations
- Array Operations
- Exercise Answers - Array Operations
- Matrix Operations
- Exercise Answers - Matrix Operations
- Data Frame Operations
- Exercise Answers - Data Frame Operations
- Factor Operations
- Exercise Answers - Factor Operations
- Operations on Text
- Exercise Answers - Operations on Text
- Operations on Dates
- Exercise Answers - Operations on Dates
- Section 5: Material
- Loops and Conditions
- Section 6: Material
- Descriptive Statistics
- Exercise Answers - Descriptive Statistics
- Probability Distributions
- Exercise Answers - Probability Distributions
- Hypothesis Testing - One and Two Sample T-tests
- Exercise Answers - Hypothesis Testing - One and Two Sample T-tests
- Hypothesis Testing - KS-test and F-test
- Exercise Answers - Hypothesis Testing - KS-test and F-test
- Linear Modeling - Working with Formula Objects
- Exercise Answers - Linear Modeling - Working with Formula Objects
- Linear Modeling - Generating a Linear Model
- Exercise Answers - Linear Modeling - Generating a Linear Model
- Linear Modeling - Updating a Linear Model
- Exercise Answers - Linear Modeling - Updating a Linear Model
- Generalized Linear Models
- Non-Linear Regression
- Exercise Answers - Non Linear Regression
- Tree Models
- Exercise Answers - Tree Models
- Section 7: Material
- Univariate Plots - I
- Exercise Answers - Univariate Plots - I
- Univariate Plots - II
- Exercise Answers - Univariate Plots - II
- Multivariate Plots - I
- Exercise Answers - Multivariate Plots - I
- Multivariate Plots - II
- Exercise Answers - Multivariate Plots - II
- Formatting a Plot - Points
- Exercise Answers - Formatting a Plot - Points
- Formatting a Plot - Lines
- Exercise Answers - Formatting a Plot - Lines
- Formatting a Plot - Regions and Layout
- Formatting a Plot - Axes
- Exercise Answers - Formatting a Plot - Axes
- Formatting a Plot - Text
- Exercise Answers - Formatting a Plot - Text
- Formatting a Plot - Color
- Exercise Answers - Formatting a Plot - Color
- Exercise Answers - Miscellaneous
- Section 8: Material
- Text files
- Exercise Answers - Text Files
- Exercise Answers - Graphics
- Section 9: Material
- Creating Functions
- Exercise Answers - Creating Functions
- Arguments of a Function
- Exercise Answers - Arguments of a Function
- Exercise Answers - Others
- Section 10: Material
Hi! You can call me Jag. I have spent most of the past 10 years implementing Statistical Forecasting Systems at major companies in North America and Asia. I graduated from Georgia Tech [Atlanta, GA, USA] with a Masters in Industrial Engineering and so have a statistics background.
As part of my prior job, I have had to work with data extensively - mining, analyzing and summarizing. I have developed routines to cleanse historical sales data for input to Statistical Forecasting algorithms. I have also had to teach Statistical Forecasting and the use of said techniques and algorithms to every client I have been at.
These days, I am an entrepreneur and am based in Mississauga, ON, Canada. I am focussed on a couple of areas, one of which is online education.
Check out my Deep Learning YouTube channel, Facebook page and Twitter page.