Algorithms for the Love of It: Difference between revisions
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emphasize prior preparation |
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= Learning | = Highly Suggested Learning Preparation = | ||
* If you come from a developers' bootcamp / didn't-study-Computer-Science-in-school background....., a big mistake many people like yourselves make is diving into a college-level Algorithms class first. I think it's much wiser to obtain a 500-900 page basic Data Structures Computer Science book, watch an online course on Coursera, and then augment that with the more comprehensive Algorithms course available on MIT. | |||
* Memorization is '''very''' important - do not believe otherwise! | |||
* If you come from a | * It is extremely easy to forget this stuff unless you find a way to involve it in your everyday life (context) - '''always always''' try to find some kind of relationship between these concepts and your every day code, no matter how obscure! | ||
Formerly [https://noisebridge.net/wiki/(affiliated_with)_Women_Who_Code_Algorithms_Study_Group algorithms study group affiliated with women who code] | Formerly [https://noisebridge.net/wiki/(affiliated_with)_Women_Who_Code_Algorithms_Study_Group algorithms study group affiliated with women who code] | ||
Latest revision as of 16:24, 8 August 2015
Because we love Computer Science!
Highly Suggested Learning Preparation
[edit | edit source]- If you come from a developers' bootcamp / didn't-study-Computer-Science-in-school background....., a big mistake many people like yourselves make is diving into a college-level Algorithms class first. I think it's much wiser to obtain a 500-900 page basic Data Structures Computer Science book, watch an online course on Coursera, and then augment that with the more comprehensive Algorithms course available on MIT.
- Memorization is very important - do not believe otherwise!
- It is extremely easy to forget this stuff unless you find a way to involve it in your everyday life (context) - always always try to find some kind of relationship between these concepts and your every day code, no matter how obscure!
Formerly algorithms study group affiliated with women who code