In this video course, we start by focusing on R's similarities with
programming languages such as basic/C/C# with loops and conditional
tests like if, so that you can feel at home and be productive straight
away.
We begin by introducing R and setting things up so that you are ready
to go using Rstudio, the associated IDE. Then we look at R as a
programming language and see how the standard things are done in it, so
you can see that it’s not that different from other programming
languages. Next, we introduce some R commands, which are very useful and
not as common in traditional languages since manipulating data is more
important in R.
Moving on, we look at an example in the Titanic dataset, which is the
kind of thing you’ll come across in R, a multidimensional collection of
variables of different types. Using the tools that we cover we can form
a picture, a story behind the data.
We then look at cleaning up data, which is what 80% of data science
is - as we rarely get a nice neat set of numbers, but mostly
unstructured junk. This is just trial and error, gradually getting to
something we can work with.
Finally, we cover statistics, which is where R originated and what it
was designed for.We begin doing some basic statistics with R to show
how it works and end up using various special features for data
visualization.
About the author
Dr. Samik Sen is a
theoretical physicist and loves thinking about hard problems. After his
PH.D., in developing computational methods to solve problems for which
no solutions existed, he began thinking about how to tackle math
problems while lecturing. He developed algorithms to generate problem
sets and solutions and learned how to create video lessons. He has since
developed a large Facebook community teaching school math around
Ireland, with associated e-learning products and a YouTube channel.
Samik is currently fascinated by machine- and deep-learning, which seem
to be world-changing on the scale of Calculus. He has been developing a
machine-learning system to do this, which has begun doing better than he
could himself (this was his original intention), spotting structures
he'd never heard of. He has a YouTube channel associated with data
science, which also provides a valuable engagement with people round the
world who look at problems from a different perspective.
