Introduction Video Lecture | What is Data Analytics? - Data & Analytics

hello and welcome to the course
introduction to data analytics my name
is NaN siddhanam I'm a faculty here at
IIT Madras Department of Management
Studies and I am Raveendran a faculty in
the computer science and engineering
department here at IIT Madras we're
really excited to be bringing you this
course the focus of this course is to
introduce you to the tools and
techniques that are used currently for
understanding data and to derive useful
knowledge from it so the course itself
follows the broad contours of the
different types of data analytics that
are there the early part of the course
is for going to focus more on data
analysis through statistical methods and
in that we will be covering descriptive
statistics which is the idea of how do
you describe data how do you represent
or summarize data and in that we will be
covering what's a visualization
techniques and so on and then we move on
to inferential statistics the context
curve is that you see the data as a
sample as a sample from a broader
universe that's generating this data and
the idea is at this point you're not
content with just summarizing the data
you really want to see something about
this broader phenomena that is
generating this data so can I make some
kind of generalization or some kind of
inference about this data so this leads
us to the main part of the course which
is machine learning and data mining so
here we'll be diving deep into the art
and science of predictive analytics in
predictive analytics we are looking to
build algorithms that build that learn
models from historic data that relate
one or more variables so note that the
emphasis here is on automatically
learning these kinds of models from the
data and therefore we'll be focusing
more on the algorithms that learn these
models rather than the models themselves
so the models these algorithms learn
should be such that they are able to
predict values about different variables
given only a subset of the variables
that describe the data in addition to
learning these models we'll also be
looking at learning interesting patterns
in the data as well as any hidden
structure that's present in the data it
will finish the course with the final
section on prescriptive analytics this
is what you might have heard as
data-driven decision
making the idea here is that you in the
earlier part of the course you've
learned to make predictions you've
learned to mind for interesting patterns
in the data you learn to make inferences
but how do you use this information to
make concrete decisions I hope this has
given you a broad overview of what we
seek to cover in this course and we
really look forward to having you join
us thank you
see you soon