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Data Scientist @ KOHO | Top 1000 Writer on Medium | MSc, MBA | https://terenceshin.com/

Advice from a Data Scientist who was in the same position

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Introduction

As a self-taught data scientist, I can confidently say that it’s very much possible to be a data scientist without a STEM degree. It won’t be an easy path, as it wasn’t for myself, but it has been worth every ounce of effort.

In this article, I wanted to share four in-depth tips for becoming a data scientist without a STEM degree. With that said, let’s dive into it!

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1. Learn the PRACTICAL pillars of data science

While “data science” is a vague term, there are a few…


Takeaways from my reflections.

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After 3 years of working as a data professional, I thought it would be a good time to share 3 of the most important lessons that I’ve learned.

I believe that these lessons are so important because they are instrumental to having a successful data science career. After reading this, you’ll realize that there’s much more to being a good data scientist than building complex models.

With that said, here are the 3 most important lessons I’ve learned in my data science career!

If you enjoy this, be sure to subscribe to never miss another article on data science guides…


Skills that will actually make you employable

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Introduction

Many “How to Data Science” courses and articles, including my own, tend to highlight fundamental skills like Statistics, Math, and Programming. Recently, however, I noticed through my own experiences that these fundamental skills can be hard to translate into practical skills that will make you employable.

Therefore, I wanted to create a unique list of practical skills that will make you employable.

The first four skills that I talk about are absolutely pivotal for any data scientist, regardless of what you specialize in. …


Learn the most important data science skill in 15 weeks

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Introduction

As I work more and more in the corporate world as a data scientist, I am increasingly convinced that mastering SQL is essential to have a successful career. That’s why, if you’ve been following my articles, I’ve been writing a lot about SQL recently.

SQL is not a hard skill to learn (i.e. SELECT FROM WHERE), but it is certainly a hard skill to perfect. …


Focusing on the most important concepts for data scientists

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What makes a good SQL coder is the ability to manipulate data in any way that they like - a big part of that is being able to manipulate dates. Dates are extremely important because businesses like to compare and assess business performance across different periods of time. Therefore, being able to manipulate dates is essential for top-tier business operations and business reporting.

In this article, we’re going to dive into 5 of the most important and most useful DATE functions in SQL along with some practical business cases in which they can be used.

1. DATE_TRUNC()

Syntax:

DATE_TRUNC(date_expression, date_part)

What does it do?

DATE_TRUNC() shortens the…


Don’t forget about traditional statistics

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Introduction

First, I’m not saying that linear regression is better than deep learning.

Second, if you know that you’re specifically interested in deep learning-related applications like computer vision, image recognition, or speech recognition, this article is probably less relevant to you.

But for everyone else, I want to give my thoughts on why I think that you’re better off learning regression analysis over deep learning. Why? Because time is a limited resource and how you allocate your time will determine how far you in your learning journey.

And so, I’m going to give my two cents on why I think you…


Types of models, key features to use, and how to evaluate one

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Introduction

As the world becomes more digitized and people are better equipped with new technologies and tools, the level of fraudulent activity continues to reach record-highs. According to a report from PwC, fraud losses totaled US$42 billion in 2020, affecting 47% of all companies in the past 24 months.

Paradoxically speaking, the same technological advancements, like big data, the cloud, and modern prediction algorithms, allows companies to tackle fraud better than ever before. …


Fully understand what a Marketing Mix Model is and how to use one

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Introduction

Marketing was always considered more of an art than a science. But with the emergence of online marketing and big data, marketing is more mathematical and methodical than ever. In fact, one of the biggest areas of opportunities for data science and machine learning applications is marketing!

This article is going to focus on an extremely prevalent and powerful marketing science technique called Marketing Mix Modeling. This article will cover what it is, why it’s so useful, how to build one in Python, and most importantly, how to interpret it.

What is a Marketing Mix Model?

A Marketing Mix Model is a modeling technique used to…


Focusing on the important concepts for data scientists.

SQL is the universal language in the data world and is the most important skill to nail down as a data professional.

The reason SQL is so important is that it is the main skill that is required during the data wrangling phase. A lot of data exploration, data manipulation, pipeline development, and dashboard creation is done through SQL.

What separates great data scientists from good data scientists is that great data scientists can wrangle data as much as the capabilities of SQL allow. …

Terence Shin

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