Difference between revisions of "Algorithms for the Love of It"

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(Learning Tips)
(emphasize prior preparation)
 
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= Learning Tips =  
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= Highly Suggested Learning Preparation =  
  
* 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!
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* 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!
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* Memorization is '''very''' important - do not believe otherwise!
* If you come from a developer bootcamp / didn't study computer science in school background - a big mistake many people make is diving into a college level algorithms class first. Most of the basics of algorithms are covered in a freshman level Data Structures class. I highly recommend shelling out for a 800 or 900 page college data structures book. The problem with online classes is that they condense too much information into short 5 minute sound bites, when what you really need is hundreds of hours of lectures and an even thicker textbook. The stanford iOS class isn't an algorithms class, but it teaches basic iOS development and is one of the best online courses out there. it is hundreds of hours of lectures and each lecture comes with hundreds of pages of notes. so yeah, that's why you aren't learning algorithms. Once I got my hands on a Data Structures text book I felt much less overwhelmed, and the lengthier explanations and examples made the coursework easier to understand. You honestly aren't going to encounter this stuff very often in your day to day life as a software engineer, but it's fun stuff to know and should be a good hobby you keep up unless you luck out and get one of those rare dream jobs at Google or academia.
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* 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 23:24, 8 August 2015

Because we love Computer Science!


Highly Suggested Learning Preparation[edit]

  • 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

Misc[edit]