Mallory Wang
2024-06-24
Teaching Assistants:
Not a bad definition! To be fair, data science means different things to different people / companies.
There isn’t a single agreed-upon definition of what data science is.
Most people agree that Data science is cross-disciplinary, drawing experience and expertise from a wide variety of different fields.
Like ChatGPT suggested, computation is an integral part of Data Science.
An equally integral part of Data Science is the theory that surrounds data, modeling, and randomness- theory that comes from the field of Statistics.
Even if you are planning on going into industry right after university, you will still need to know some of the theory.
So, how does this course factor into the discourse surrounding Data Science?
From the course description:
Introduction to data science. Concepts of statistical thinking. Topics include random variables, sampling distributions, hypothesis testing, correlation and regression. Visualizing, analyzing and interpreting real world data using Python. Computing labs required.
We will then devote some time to talking about Probability, which is in many ways the theory behind randomness and uncertainty.
Next, we will use Inferential Statistics to discuss how we can use data to draw conclusions (i.e. inferences) about the world around us.
Then, we will discuss a topic known as Regression which will be our first (and only, for this class) foray into statistical modeling.
We will then take a closer look at how data is collected, and the various strategies that can be utilized when trying to collect data of our own.
However, wherever there is data, there is the need for a Data Scientist (or, at least, some of the principles from Data Science).
Here’s a perhaps more pragmatic answer: even if you think you want to go straight into industry right after this course, no company wants to hire someone to just mindlessly crunch numbers - though computing experience is absolutely crucial in making yourself a good candidate, employers would much rather have someone who is both skilled at running code but also understands why they are running the code they are running!