How I Would Learn Data Science with ChatGPT (If I Could Start Over)
Learning how to learn is one of the most useful skills you can cultivate.
When I first started teaching myself programming and data science in 2018, I enrolled into countless online courses. Every time I completed a course and got a certificate, I’d get a momentary feeling of accomplishment.
As though I’d learnt something new.
That feeling, however, was always fleeting, because every time I tried to put what I learnt into practice, I failed.
Theoretically, I understood how classes, methods, and object-oriented programming worked. I knew the difference between random forests and decision trees, and grid search versus Bayesian optimization.
Yet, I wasn’t able to work with real datasets.
Every time I tried to build a new project, I would come across a roadblock and encounter yet another topic I didn’t know about.
Then I’d go down a rabbit-hole of taking new online courses to fill the gaps in my knowledge.
This endless cycle is known as the tutorial-trap, and I was stuck in it for two years.
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