Introduction to R (Udemy.com)
Learn the core fundamentals of the R language for interactive use as well as programming
Created by: Jagannath Rajagopal
Last updated April 2014
What you will learn
- 90 videos (15+ hours)
- To educate you on the fundamentals of R
- 140+ exercise problems
- To accelerate your learning of R through practice
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.5 out of 5higher than 46% of them
- Reviews1,978#93 of 462 by number of reviews
- Length14.9 hourslonger than 70% of them
- Last updatedApril 2014earlier than 100% of them
Course 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.
Instructor Details
- 4.5 Rating
1,978 Reviews
Jagannath Rajagopal
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.
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Reviews
By Alpesh Patel on 7/25/2020
This is completely new course for me, as I am a beginner, but the way it has been explained in each learning material is highly appreciated for creator kind effort. I gained a basic understanding of it and practice can help me to build more understanding of it. Thank you
By Harshit Paliwal on 6/12/2020
A good choice for beginners, a small thing which i wanna mention is that the whole course is covered entirely by programming in console, and there has been a very less usage of R script, which i think should also be made familiar to the students to work with. Otherwise, based on content the course is excellent.
By Antonio Desdier on 4/6/2020
The course is well put together. Too many tutorial are repetitive as that they repeat the same basic material assuming that you are starting from scratch. It will take a bit of time to digest the material that was presented. However, I feel that it would be worth it.
By Mohitkumar Dhiman on 2/6/2018
My overall experience was amazing. Before this course, I was very new to R and R programming. After attending this course, I feel that I am now comfortable with R programming as all the fundamental concepts were covered aptly in this course. I would recommend beginners to take up this course. It will help them to be familiar with R environment.
By Doc Skel on 6/20/2017
I am now up and running in R and that is the point of the course. One piece of advice for anyone about to take the course that I feel should have been given at the start: do not simply use the command line in the Console for all your coding, as in the course videos. It is far better to do some of your coding in a script that you can save. Then you have a permanent copy of your code that you can review later, copy and paste into new scripts, etc.
By Santiago Oberto on 1/18/2017
Muy didáctico. Bien orientado a R, aunque por momentos (sobre todo en el capítulo de estadística) estaría bueno que se tome unos minutos para dar un poco más de pautas teóricas de lo que se expica (los usuarios lo podemos resolver a través de google, o consultando con alguien que sepa del tema). Fuera de eso, los ejemplos claros, conforme con lo que esperaba ver. Muuy buena duración de los videos. Por momentos un poco largos, pero es preferible que explique bien y no que sea corto y no explique nada! Muy bueno!!
By Samuel Carey on 7/17/2016
Overall, I thought the course was very good. It covered a lot of concepts and was very informative. The only thing I would change is being a little more thorough on everything going on in the R code when showing examples. I know the idea is to focus on what you are teaching for that lesson, but sometimes, I would have to pause the video and really focus on what else was going on in the code to truly understand what I should be seeing. So I would be distracted from the main point of the lesson, when it could be a quick explanation taking a few more seconds. Other than that, the course covered a lot of information which was great, since I have never used R before.
By Micah Shull on 2/14/2016
Perfect intro to R. Pace is slow and methodical, with examples and exercises. But, provides much more information than other classes I've been through on Coursera. Teacher offers assistance and guidance. Great way to lay the foundation for a future in R!
By John on 12/14/2015
Jag, the Instructor, really knows his subject and does a very good of job teaching it. The pace he sets is a bit quick and it would help to print out the lecture materials, which he provides, and use them as a guide while watching the videos lessons.
By Mahmoud Rabie on 12/2/2015
the course is good and the examples are very good too, but the only problem and the major one I faced in this course was with the statistics part as I don't know most of the topics explained there, and I think that this part can be just a small overview and not to take big part from the course in explaining it, I think the instructor should focus more on learning R though playing with the basic topics in statistics
Quality Score
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Overall Score : 90 / 100






