From Mickey Mouse to Machine Learning

I do love numbers. And I do love stories. Up until a couple of years ago, I would have never thought I could have turned these two passions into a profession. If I caught your attention, let me tell you my story.


I am from a small town in Italy. At the end of the 80s only few families had a personal computer at home. I was lucky enough to have one, since both my parents are engineers. And, as any curious kid, I was absolutely intrigued by that grey machine — photographic evidence below.

I remember that I was mainly playing floppy-disk video-games — Zool (link for the youngster here) was my favourite. If you are wondering, this is not the story of a little kid that starts coding at the age of five, and then go out and build a multi-billion empire from his garage. My encounter with programming would have eventually arrived, but not at this stage.

One day I saw my mom working on something at the computer. Now I know she was making slides for her students — I think she actually was one of the first persons to user PowerPoint — but, at that time, that PowerPoint programme looked like a fantastic drawing tool to me. I recall I spent the following days drawing my first Mickey Mouse-like comics in PowerPoint. I was so excited to use speech bubbles — I really felt like Walt Disney. Little I knew at that time that my first PowerPoint story would have had such a profound impact on my life.


Let’s fast forward almost twenty years later. I am in London, all dressed up to start my first (real) job. As most of my fellow Business and Management graduates I am going to work as a strategy consultant in a multinational firm. I quickly discover that being good at using PowerPoint (again) and Excel will make me succeed.

This is the time when I discover the importance of two elements: scalability and clarity. The first one refers to learning how to do things faster (from using keyboard shortcuts to linking a presentation to a data source so that it can be automatically refreshed without re-doing it every time). The second one, more nuanced, is the ability to convey a message, a concept, a story. This is the time when I realized that tables filled with numbers tell nothing, while charts do.


Over the years, I stock up experience on presentations, visualisations, Excel, etc.. However, my presentations become progressively different from those of the others; I use very few words, mainly pictures and charts, compared to slides packed with data, tables and many — too many — words!

However, even if my work is fully appreciated by my colleagues, I can see that “state-of-the-art” presentations and visualisations are far away from my standards. I want to build interactive charts, cross-filtered dashboards but every time I see explanations on how to do them…well, I need to code.

Deep in my mind I know that, sooner or later, I should learn how to code. I ask a couple of friends which language I should focus on, and all of them point me to one candidate: Python. Being a millennial, I ask my friend Google who — with a targeted advertising — points me to a website called Udacity and an online course called Nanodegree — Introduction to Programming. This is the beginning of my love affair with Udacity.

The true aha moment, however, comes with my second Udacity course, the Nanodegree — Data Analyst. This is mind-blowing. First of all, I discover that all the operations I was doing in Excel are unbelievably more scalable when done in Python. Secondly, I find out that everything I had in my mind about visualisations and storytelling with data is actually validated by theories, and by “Data-Viz wizards”! Thirdly, I learn about something I never heard before: machine learning. I am literally stunned by all this overflow of awesome stuff.

For the first time in my life, I am really sure about what I want to do: Data Science. That is why I subsequently enrol in the Deep Learning Foundations nanodegree, in the Machine Learning Engineer nanodegree and I am planning to start the Artificial Intelligence Engineer nanodegree soon. Thanks to the practical approach of Udacity’s courses, I manage to complete projects that I thought would have been impossible without prior Computer Science experience. For example, I built a convolutional neural network to classify images, I built a visualisation on D3.js (this is cool stuff), I generated TV scripts using Recurrent Neural Networks!


Today I am working as a Data Scientist in a global financial services company. I managed to overcome apparent difficulties like not having studied Computer Science at college. Probably my story is an example of serendipity. Clearly I was lucky, but I like to think that there were some non-coincidental events that shaped who I am.

I understood that passion is the truly unique driving force in your professional life. If you have no passion for what you do, you will never be at the top. Invest time in trying to understand what you truly like; learning how to do it will be easy!