A complete overview of the most essential components of data science and how to master them

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If you are reading this article, it means that you are hoping to become a great data scientist and you just don’t know where to start. Although I am not an industry expert, I have been creating my own data science path for over 2 years now. I have been through 9-month long research projects at University College London, to real-life AI projects at a hospital, to multiple Kaggle competitions, and finally to writing data science articles here. And I think it’s always better to get advice from someone who isn’t too far down the line, someone who went through these challenges recently and can give you some tips to get through them faster.

In this article, I will do my best to layout the most essential areas that you need to look at in order to start diving deep into Data Science. I will also try to layout the best learning resources to do so.

1. Essential theoretical knowledge of statistics and calculus

I think you kind of expected this to be the first one, but before you just skip to the other section or just another article, let me tell you why. An okay Data Scientist learns how to use a bunch of tools like PowerBI, Scikitlearn, etc… This will be fine for building baseline models, but then you will find out that it’s not enough and you need to improve your model. This brings us to reading ML research papers, and you have to trust me on this, you will not understand most of the ML papers if you don’t understand essential statistics. And if you don’t understand most of the papers, you probably won’t be able to implement them and improve them, which is a big issue.

I remember struggling with understanding ML papers at university, it used to take me a few days if not weeks to fully grasp them. However, this all changed when I spent a few weeks learning the fundamentals of statistics and calculus. Now, I can easily digest those papers in an hour or 2. If you haven’t already done so, you will not believe how much those papers are relying on those foundations.

One very important note that I want to stress here is that I am not asking you to be an expert in these foundations. This is what most people struggled with in high school, being good at math and statistics to get through an exam. You don’t need this here, you just need to understand the foundations to digest the research papers. Understanding them is much easier than…

Continue reading: https://towardsdatascience.com/top-4-things-you-need-to-know-to-get-started-in-data-science-2021-cb8185472b5c?source=rss—-7f60cf5620c9—4

Source: towardsdatascience.com