The more you learn, the more you realise how much there is left to learn.
I was reminded of this important lesson today when I was trying to use a smarter way to populate an Excel report and came up against some challenges. Even though the way I was preparing the report was much better than the previous version, it was also right on the edge of my knowledge and abilities and so when something didn’t work, I didn’t know a way around it.
Another recent example of this is my misunderstanding of Machine Learning, which I confused with training AI. Machine Learning is more to do with statistics than it is to do with automating tasks (although it can help there too).
Finally, my ambitions and ideas have almost always been above what I was currently aware of and capable of. The more I look into tools for things like data scraping, the more I realise I don’t really know what I’m looking at and may be going in the wrong direction entirely for a while.
But when compared to where I was a year ago, I’m still ahead!
So while it’s important to be as aware of what you don’t know as what you do, it’s also important to remember what you’ve learned along the way.
Today, I am much nearer my goal of gaining all of the skills of a Data Scientist than I was yesterday. A year ago I didn’t even think about becoming a Data Scientist, my ambition was to be a badass analyst back then.
The more you learn, the more you realise you still have to learn.
And I’m looking forward to it!