It’s been over a year since my last blog entry, and a lot of things happened in my life during that time. I’ve changed my job, travelled to few continents for the first time and finally took a real vacation. But the most important aspect that is the topic of this post and of which I’m extremely proud is me changing my career field. I stopped being a software developer and am now a data scientist. Nowadays it doesn’t sound like something special. Data science, machine learning and AI, in particular, are the areas that seduce hundreds if not thousands of software engineers every year. It’s no brainer why – there’s clearly the future there and being a part of something this big and influential is appealing to practically everyone. Let me tell you how I got here.
Since I was a little girl…
… I wanted to do maths. My dad is a retired mathematics teacher, but when he was younger, he decided to introduce me my sister and me to the topic very early. We started with simple calculations like adding and subtracting, went through multiplication table, dividing numbers. This is when the fun has begun. Wait, have I just said fun? Indeed, back in those days, I couldn’t wait till the next weekend when we could again spend the whole morning playing with maths. It’s my dad who made it entertaining, and we were not for even a moment under the impression that this required hard work. Even though it did, it felt like the right kind.
Finally, the time has come for us to conquer the world of square roots. At that moment, at the age of 6, I had my first career crisis. I remember this very clearly. Imagine, I was just told that, to find out the square root of let’s say number 36, instead of calculating I need to go through the process of few tries. I first need to find the number, i.e. 3, and square it, which gives me the number 9. I repeat these steps until I identify the result that equals with my original 36. This mind switch was quite exhaustive for my little brain. But I wasn’t to give up and couldn’t believe that there is no other way.
So, I invented one. Long story short I discovered that when you add odd numbers sequentially, you’re always getting a result that has an integer square root. Check it with our 36:
This rule can be generalised like this:
Of course, at that time I was nowhere near this kind of formalisation. I didn’t even know what an odd number was, not to mention how to write down my findings. So far, all my discoveries were safe and sound in my head. But I was hooked, and that very moment made mathematics the love of my life.
Attraction and practicality
When I started my formal education, the school was all about maths. It was much more than that. Mathematics defined me, became the part of my identity, of who I was. Everyone was convinced that my further career choices would be tightly connected with the field. Probably even academia related. But when the time of the decisions came I went for something more practical. After endless conversations with my family, teachers and peers I decided on studying computer science.
Of course, this choice resulted in the curriculum that had some lectures that introduced me to the higher mathematics. It even generated a second wave of my love to the field. I’ve learned it wasn’t at all about the numbers and that in reality, they are used mostly when indexing theorems. But computer science wasn’t enough, so eventually, I started a second faculty – mathematics. Unfortunately, this configuration didn’t last long, studying two subjects and working full time was a little bit too much for me.
I was missing it like crazy, so instead of putting myself through the path of too many duties again, I decided to do something data related when working on my MSc dissertation. I guess today you would say I was doing data science and machine learning. At that time it was called data mining. I graduated and decided to continue the project through the PhD studies.
That was quite an adventure. Classes to attend, classes to teach, research and a full-time job outside of the academia. After few years all I had to do was to write the dissertation itself. I was investigating topics like classification problem, fuzzy rules and evolutionary algorithms. And then the decision about moving to London came along, and I had to put my work on pause.
Software engineering gave me a great background, but it was London what kicked off my career in data. Armed with the experience and skills I gained while working with many companies, academia, various projects, in different roles, teams and people in general, I finally decided to focus on data science path.
As a result, now I get a lot of queries and request from attendees of my talks, former colleagues and fellow developers on how did it happen. They ask what the best way to approach the world of data science is, where to go to continue with more advanced topics and how to stay committed. The most common question, though, is if there is this one resource, either a book, a website or a course that will give you the comprehensive knowledge or at least a decent background.
The answer is: yes and no. Of course, the world (and the internet specifically) is full of content on every topic; data science is no exception. There is no excuse for not reaching and exploring what’s out there. But it comes with the price, this amount of information can be intimidating. You can say we have a big data issue with big data topics, as so many resources bring a lot of noise, repetitions and simply too much information.
This is where my idea comes from. For people with the similar background to mine, I’m planning to create a series of blog posts dedicated to data, machine learning and AI. I will walk you through the basics, dive in into topics I find interesting, explore the real-world applications and point out useful resources. My goal is not to add to the noise and repeat what’s already out there. I would rather like to organise the knowledge, so you find it easier to decide where to go next.
New content will result in the new structure of the page, maybe even rebranding. I am also adding few workshops to my portfolio, so if you or your company are interested in starting your adventure with data or exploring more advanced material – have a look and don’t hesitate to contact me.
I feel excited and cannot wait to write my first entry of the new series. Is there anything you would like me to write on?