Data Science Contact Week 1: Finished!

My first face to face contact week with the university professors is over.

In some ways I’m relieved because the hours have been long, as has the commute, and the work has been tiring.

But I will also miss it, because I’ve enjoyed the structured learning as well as collaborating and bonding with fellow students.

I’ve made a lot of notes and have of lot of things to go back over. Many things I was worried about before the week began are now much less scary. Programming is going to be fine, I’ll translate what I know in VBA and just play about to learn the rest.

Linear algebra is certainly going to be a challenge, but that just means I need to spend more time on it.

My biggest take away from the experience is that when I apply myself and put in the hours, I end up gaining a lot more than I thought I would. It’s a nice feeling to begin understanding something brand new after just a couple of days. It’s a shame that all of the teaching has to be bundled into a week at a time spread throughout the year, but that also means I can’t get complacent. There is a lot to prepare for the next contact week in January and everyone needs to be up to a certain level.

I definitely saw that some people were held back while the rest of the class catches up, and that’s a shame. I was one of those holding others back, particularly in the mathematical areas (which there are a lot of!).

Anyway, I am far more aware of where my weaknesses lie now AND what I can do about them, so I’m motivated to keep up the momentum now.

I’m even becoming accustomed to using Jupyter notebooks now, which a few months ago appeared to me as some sort of special club you joined when you graduated Python school!

Anyway, I’m off to study some A-level statistics (yes, this is an area I suck in), so I’ll catch you on the flip side.

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