So, welcome to the course on Mathematics for
Data Science. This is the 1st course of two
courses which are there in the foundational
setting. So, why are we studying mathematics
in this programming and data science course
is because data science actually combines
mathematics, statistics and computing. So,
without a good background in mathematics,
it is not possible to really appreciate many
of the ideas that go into data science.
So, in this 1st course in mathematics for
data science, we will basically be covering
material which may be familiar to many of
you. We will start with fairly basic things
about numbers, sets, relations and functions.
This is just to bring everybody onto the same
page in terms of terminology and notation.
Many of these concepts as we said you would
already know or even if you have not seen
it for some time, this refresher should tell
you what you need to know.
Having got these basics under our belt, we
will do some coordinate geometry. So, we will
look at how to draw lines and how to get the
slope of a line, how to calculate the angles
between two lines and so on. So, these are
again things which you might have studied
in school and you may have forgotten. So,
it is good to brush up and remind ourselves
of how these things work.
We will move on from lines to quadratic equations.
So, if you remember lines represent linear
equations, quadratic equations have a square
term if you draw them, they look like parabolas.
So, we will look at quadratic equations and
then, we will generalize to higher power so,
these are what are called polynomials. So,
these are all functions which we can draw
as graphs in the sense of coordinate geometry,
but we can also analyze them in many different
ways and functions will be quite essential
in our study of data science. So, moving on
from polynomials, we have functions which
are not polynomials; those that grow very
fast, these are exponentials and those that
grow very slowly, these are logarithms.
So, to summarize we will be looking at large
variety of functions starting from lines and
going through polynomials to exponentials
and logarithms. And finally, we will move
to something which perhaps you have not seen
in school which is a different form of graph.
So, this is not the kind of graph where you
have an x axis and a y axis and you draw a
curve, explaining the relationship between
x and y rather this is a graph of the kind
you see when you look at for example, a map
of an airline timetable. So, in this graph,
we have nodes representing points of interest
and edges representing connections.
So, one example is a road network or an airline
network, but these edges can also represent
other relations. For example, we can think
of an organization and we can think of employees
and they are connected to the manager that
they report to. So, we will look at graphs,
how to represent data as graphs and some simple
manipulation on graphs algorithmically.
So, I hope you will enjoy this course. I am
sure that a lot of it will be familiar to
you, but I hope that you will also find something
new and a new perspective on things that you
already know and with this, you should have
a good foundation for all the courses that
come up ahead.
Thank you.
