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In college I had tried to get into programming (including taking a CS class) and had, each time, bounced off (not because I couldn't get it, but tutorials seeme
by spenvo 10y ago
In college I had tried to get into programming (including taking a CS class) and had, each time, bounced off (not because I couldn't get it, but tutorials seemed boring and a passion wasn't ignited).
Fast forward to after college, I found myself at a career-y job I disliked. Each lunch break I loaded up my (shiny new 2011) Macbook Air with a few tabs-worth of chapters of How to Think Like a Computer Scientist [0] and headed to a Wendy's that didn't have an internet connection. So, for 45 minutes I could eat my spicy chicken nuggets and apply what I was learning from the book in console at a Python command line. It was so simple and fun, I was hooked. Within a month I was taking on programming-related responsibilities at work, soon thereafter auditing a class at Uni (I specifically chose cause it interested me), and within 4-5 months was being paid by my professor (from audited class) for web dev grant work, and a few more months and I was being paid as a developer by the University directly. The rest is history.
I think one key part of why it stuck the fourth time was because my routine allowed for 45+ minutes of time away from the internet each day with learning materials. The satisfaction of learning is incredible but more of a "slow drip" compared to the kind of instant satisfaction one can get by opening Netflix, Facebook, or whatever. Going without the latter during a key period I think changed my life.
[0] - http://openbookproject.net/thinkcs/python/english3e/ http://openbookproject.net/thinkcs/python/english3e/
- hyperpallium 10y ago> tutorials seemed boring and a passion wasn't ignited > job I disliked ... How to Think Like a Computer Scientist [0] ... and apply what I was learning from the book in console at a Python command line. It was so simple and fun I'm struck by how the right guidance was also helpful. Actually making something new happen is rewarding (py console), you experience your progress. But it can be tricky to divide a topic into bite-sized things, that can be experienced. That's where guidance helps. Unfortunately, some topics have so many layers, they're difficult to break down into these learnable, rewarding chunks (e.g. computational fluid dynamics). So (if you don't mind a reframing) while the slow drip of a consistent routine over a long period was crucial, each drop gave fairly quick (though not immediate) gratification.