Become a highly effective data scientist, no matter what company you work with.
Learn how to provide value with math and statistic to any business, no matter the size.
From advanced feature engineering and sustainable machine learning operations to managing social and cultural dynamics inside the company. This course will teach you everything you need to be an effective one-man data science army to be reckoned with.
We will introduce you to the different growth stages companies have, and the qualitative and quantitative information they need in said stages.
We will walk you through Sean Ellis, founder of dropbox’s product-market fit roadmap, and teach you exactly what metrics and qualitative information is needed to advance in the business growth pyramid , from product market fit, to transition of growth and viral growth. You will understand exactly what information needs to be gathered and how to obtain it.
This knowledge will proove vital for being able to adapt yourself in the future to any business and industry you might work in, and being able to properly audit knowledge architectures and fill any knowledge gaps that your company might have. It will also proove to be essential to maximize your feature engineering capabilities.
We will show you a framework to structure any possible data science project you might have to work, to maximize it’s chances of success. This framework will also allow you to make sure that “success” is aligned with actually providing value to the company, hopefully ROI.
We will also show you the most comprehensive list of possible data science and math applications used across multiple different industries, so you have an exhaustive knowledge of all the actual possibilities math holds for businesses. This will allow you to diagnose effectively what possible projects your company can tackle with hopes of success, and how to start working said projects.
Any respectable one-man army data scientist should also have the engineering knowledge to make its solutions ready for productization in a scalable, reproducible, and robust manner. Here we will teach you everything you need in the ML-Ops methodology so you can start making your projects production-ready and reproducible, as any true business-driven data scientist should aspire to.
A very self-explainable title. For me, feature engineering is probably one of the two most critical skills a data scientist could have, and the one that actually names the profession. This chapter we will tackle how to take your feature engineering skills to the next level to be elite level, specially when working dynamic and chaotic systems where humans play a key role in it’s outcomes (meaning: any system where business stakeholders are involved).
The other critical skill a data scientist should have. There is no data-driven strategy if you can’t actually demonstrate hypothesis and create tests that proove and reduce risk in the decision making process. In this chapter we will make you a true statistician.
How to lead a data science project, how to manage it’s risks, potential outcomes, business expectations and stakeholders, we will cover in this chapter all the essential soft skills a data scientist needs, and we will teach you how to effectively integrate with the company culture.
No matter how good a data scientist you are, you are not transforming the company on your own, you will have to win departments and coworkers over and sell them on your vision and the benefits of being data-driven. This chapter will guide you.
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At least you should not be scared of it, we won’t be coding too much in this course since I’m not going to teach you how to implement step by step any of the projects. However some code snippets are referenced to show how different tools work, and as a data scientist, you should know programming. This is a business and data science course designed for a technical audience.
Yes. You are expected to have an understanding of how and why data is used, and how data analysis is done. Ideally you should have trained, even in a toy dataset, a machine learning algorithm in a notebook. This is a course for data scientists or people interested in becoming one. If you have no idea of data and tech but are interested in starting in this industry, my data-driven businessman course will tell you everything you need to know.
No! never! , you will never see that money back !
Just kidding, of course! you have a 30 day refund guarantee, no questions asked.
I might ask you for some feedback though, I personally recommend you to try and take advantage of the mentoring sessions before refunding, that way you can help me improve too! :), if even after talking one on one with me you still don’t find your money’s worth, that’s totally fine.
If you don’t want to meet and just want your money back, no questions asked, that’s fine too.
Stefano Benco, founder of mathforbusiness.com
Hi, my name is Stefano Benco, businessman, data scientist, beach lover and Hawaiian shirt collector. As of now, I have been working for more than 5 years as a data and tech consultant for multiple agencies and international clients, which I started doing while finishing my two business degrees.
I have worked with the smallest tiny projects you might imagine, and with awesome fortune 500 multinational companies, I have seen and implemented firsthand many projects in data science and big data, and i’m here to teach you, through my experience everything you need to know to find success with it.
I’m a businessman that got into the data industry to make money and make any project I’m in, find competitive unfair advantages. Along the way, I fell in love with math and tech.
I think of myself as the best bridge between the business and the data world you will ever find, as I know first-hand what is the important things to learn and what is the bull. I will teach you everything you might not know, and that you actually need, and skip the useless details.
I hope that not only will I be able to teach you what you want to know, but also, help you fall in love with this beautiful industry and the science behind it.