Love for Data
I am the master of my fate – and the captain of my destiny | Nelson Mandela
If a man neglects education, he walks lame to the end of his life | Plato
While pursuing a career in Data Science – or for any field for that manner – a few things are important to notice. As Data Science has been called “the sexiest job in the 21s century”, many people want to learn it and (in my opinion) earn more money. But why is learning Data Science nothing different than learning to be an engineer, car repair man, doctor, lawyer, etc.?
For me the main factor is: ‘Do what you love’. This means, you should do what interests you, what makes you wake up in the morning all excited and full of energy. And that is data for me. My entire life I have been, unknowingly, working with data. From a young child in keeping track of cars passing by my bedroom window, to keeping track of project progress to analyze data to improve performance of the company.
And only the last few years I have been introduced to something that is called ‘Data Science’ and I think it was love on first sight. Since then, my learning curve has exponentially grown. But how did I decide what to do? Loving something is one thing, but showing your love is something else.
My learning path
First, I read a lot of things about this ‘new’ thing, called Data Science. That got me introduced to a few courses online, which I followed. But, it was a lot of abracadabra for me. Brushing mathematics, something called as Machine Learning, Statistics…that was quite some take in. But, as I am in love, you keep on going. The love is strong. I started a course with Microsoft, called Data Science. Completed that in 3 months and I felt a lot of things got clearer to me, but still not good enough. Statistics was certainly not my strongest side, especially not doing it in another language (my mother tongue is Dutch). So, looking at my deviations, I followed some specific courses on statistics, bought some books and kept on reading, learning and acquiring knowledge. The practical part is still missing at this point. Then I signed up for the Post Graduate diploma in Data Science. Very excited to refresh the earlier acquired knowledge, and my love for data, I started the course and learned a great deal. Not only knowledge about Data Science, as in knowledge about Statistics, Domain knowledge and Machine Learning, but moreover where the pitfalls are.
And getting that kind of knowledge, is maybe even more valuable, then actually learning methods, models and equations. That knowledge I will explain below.
Something you can learn, or acquire knowledge of, is working with peers. Learning from other people has been a great asset for me over the past few years. I used to keep things for myself, but I have started to talk to people, share ideas, share knowledge and mostly have fun with each other doing so. The knowledge I have gained, while working and talking to peers is immense. Knowing that you’re not the only one facing difficulties with certain topics, sharing information and so on and so on.
As my dad once said to me: “You have to network”. I fully disagreed at that time (as sons normally do), but the value of networking is one of the biggest assets in my opinion. Looking back at my career, I have never done any official job interview to get a job. All of it has come my way by networking. And that networking I am extending day by day. Connecting with people, be active on social media (Twitter, LinkedIn, blogging) and be part of interesting (local) groups. Without networking it is really difficult to get where you want to go.
Something most people are lacking, including me. Having domain knowledge is key. Without it, it doesn’t make any sense what you’re doing, at least, you will not excel in my opinion. As I keep on saying: working with DNA strings and predicting if someone might get cancer, is something I might be able to conduct, but mostly by missing specific domain knowledge, I think I have nothing interesting to mention about it. Of course I have gained my share of experience, and with that acquired some kind of domain knowledge, but it’s very general. If you’re lacking the domain knowledge, start learning.
Being part of a community, is one of the main things to do. It will assure the above-mentioned areas, as you will meet and talk to like-minded people. It will give you peers (work together on data projects), it will give you a platform of networking (people learning from you, you learn from others) and it gives you access to a lot of people in different domains, of which you can learn again.
Therefore, in my love for data, I want to learn, share and make it the most beautiful thing in the world.