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Terence Shin, MSc, MBA
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Towards Data Science
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Coming from a non-technical background, I was more-or-less on my own.
When I first started my data science journey, I spent a chunk of time figuring out where to even begin, what I should learn first, and what resources I should use.
Over the past two years, I’ve learned several things that I wish someone could have told me, like whether to focus on programming or statistics first, what resources I should use to learn new skills, how I should approach learning new skills, etc…
Therefore, this article aims to provide some direction and insights for those who are learning data science.
My assumption is that as an aspiring Data Scientist, you’ll want to fully understand the concepts and details of various machine learning algorithms, data science concepts, and so forth.
Therefore, I recommend that you start with the building blocks before you even look at machine learning algorithms or data science applications. If you don’t have a basic understanding of calculus & integrals, linear algebra, and statistics, you’ll have a hard time understanding the mechanics behind various algorithms. Likewise, if you don’t have a basic understanding of Python, you’ll have a hard time implementing your knowledge in real-life applications.
Below is the order of topics that I recommend you go through:
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Towards Data Science
Data Scientist @ Cash App | Health fanatic | Educator | https://www.linkedin.com/in/terenceshin/
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