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 combines mathematics, statistics, and computing.
So, without a good background in mathematics, it is not possible to appreciate many of the ideas that go into data science.
So, in this 1st course in mathematics for data science, we will be covering material that 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 them 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 a higher power so, these are what are called polynomials.
So, these are all functions that 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 that are not polynomials; those that grow very fast, these are exponentials, and those that grow very slowly, are logarithms.
So, to summarize we will be looking at a 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 of 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.
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