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Think like a data scientist with this essential statistical concept

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In almost any role in a business, you’ll have to make estimations:

  • In marketing, you have to estimate ROIs for future campaigns.
  • In supply chain management, you have to forecast (estimate) the amount of inventory you’ll need.
  • In product development, confidence intervals are important for determining reliable specifications of a product.

Now it’s one thing to make an estimation, but it’s another to give make an estimation and provide a confidence level.

Consider the following…

  • Statement A: I estimated that we’ll do $500,000 in sales next year.
  • Statement B: I estimated and I am 95% confidence that our sales next year will fall between $450,000 and $550,000. …

Tips to be an efficient and a fast learner

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I wanted to write this article because I’ve gotten a lot of questions around how to approach learning data science, and I understand the struggle. It’s really overwhelming at the start, especially when you find out that you have to learn programming, statistics, mathematics, and so on. It seems like the list is endless, but trust me when I say that it’s not as bad as you think.

My goal is two-fold:

  1. I want to smoothen your learning journey by giving some direction and tips
  2. I want to share with you my tips that helped me learn at a faster pace

Study smart, not hard.

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Statistics can feel really overwhelming at times, and it’s no surprise as the practice of statistics has been around for thousands of years!

When it comes to data science interviews, however, there are only so many concepts that interviewers test. After going through hundreds and hundreds of data science interview questions, I compiled the 10 statistical concepts that came up the most often.

In this article, I’m going to go over these 10 concepts, what they’re all about, and why they’re so important.

With that said, here we go!

1) P-values

The most technical and precise definition of a p-value is that it is the probability of achieving a result that’s just as extreme or more extreme than the result if the null hypothesis is too. …

Recommended by some of the largest data leaders in the world

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Photo by Jude Beck on Unsplash


Happy New Year!

To kick off 2021, I wanted to share the seven most recommended data science skills from dozens of interactions and discussions with some of the largest data leaders in the world, including the Head of Data & Analytics @ Google, the Senior Director of Engineering @ NVIDIA, and the VP of Data Science and Engineering @ Wealthsimple.

While this article may be more anecdotal, I feel like this article shares a valuable perspective. …

Step-by-step projects that you can add to your resume

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Keras. If you’re entering the machine learning field or have taken on the challenge of learning how to program in Python, you might have heard of this library, and its industry standard companion Tensorflow.

Keras is used for thousands of professional applications all across the globe, and technologies that take advantage of the Keras API are probably embedded in various apps in your smartphone and computer.

So, what is Keras, and why do I believe that it is an absolutely essential API and library to learn, whether you are a beginner coder or seasoned Python pro? Let’s find out.

What exactly is Keras?

Keras is a machine learning API and library built for integration with Python programs. It contains various modules and shortcuts for building and testing your own machine learning models, at virtually any level of intensity. It can be used for very simple, surface learning tasks, or heavy deep learning tasks where complex analysis is required. …

#2. Don’t feel sorry for yourself.

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If you’re an over-thinker or a perfectionist, it’s very easy to get lost in your own thoughts. I happen to be both. On top of that, I’m still trying to figure out who I am as I navigate through my twenties.

I know the feeling of spiraling downwards so deep that you don’t see a way to get out. Sometimes I get so lost in my head that I question everything that I do which is an extremely toxic thing to do.

That being said, I’ve also learned a couple of things that I try to constantly remind myself so that I don’t fall into the trap of self-deprecating introspection. While I’m not a psychologist, I have found that nailing these ideas in my head has helped keep me away from my negative thoughts. …

Learn something every week for 52 weeks!

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“Everyone wants to eat, but few are willing to hunt”


If you want to be a data scientist but haven’t yet made the commitment, now is the time.

Last year, I made a commitment to learn something new about data science every week for 52 weeks, and I think that was one of the best decisions I’ve ever made. You’d be surprised at how far you can get in a year.

And so, I’m presenting to you a complete 52 weeks curriculum that you can do in 2021 as a new years resolution! …

Relevant and valuable data science projects that you can do in a day!

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As you approach the holidays, you’ll finally have time to sip on some hot chocolate, sit by the fireplace, and watch hours and hours of Christmas movies.

Or… You can spend your time doing some awesome data science projects! Because what’s a better way to spend your time than adding another personal project to your GitHub repo ;)

And so, I give you 12 data science projects for 12 days of Christmas! Each one can be finished in a day and each will guarantee to teach you valuable and applicable skills.

With that said, let’s dive into it:

1. Python Simulations

A Googler, Adjunct Professor at IE Business School, guest lecturer, public speaker, and thought leader!

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Image provided by Christina


The same way that I write articles to share my advice and opinions for others to learn from, I personally like to reach out to others to hear about their story, advice, and wisdom to learn from them as well!

Christina Stathopoulos is actually one of the first few people that recognized my writing and shared one of my articles back in March! Since then, she has selflessly provided me with guidance and support around my career and data analytics in general.

And so, I thought it would be extremely valuable to give Christina an opportunity to share some of her experiences and wisdom with the rest of you! …

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